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Additional newsletters available at http://www.ima.umn.edu/newsletters
IMA Newsletter #424
February 2012
2011-2012 Program
See http://www.ima.umn.edu/2011-2012/ for a full description of the 2011-2012 program on Mathematics of Information.
IMA Events
IMA Workshop
Second Abel Conference: A Celebration of John Milnor
January 30 - February 1, 2012
Organizers: Alejandro Adem (University of British Columbia), Geir Ellingsrud (University of Oslo), Michael J. Hopkins (Harvard University), Robion Kirby (University of California), James Stasheff (University of Pennsylvania)Summit on 2007-08 Thematic Year on the Mathematics of Molecular and Cellular Biology
February 5-7, 2012
Organizers: Fadil Santosa (University of Minnesota Twin Cities), De Witt L. Sumners (Florida State University)IMA Annual Program Year Workshop
Group Testing Designs, Algorithms, and Applications to Biology
February 13-17, 2012
Organizers: Yaniv Erlich (Whitehead Institute for Biomedical Research), Anna Gilbert (AT&T Laboratories - Research), Olgica Milenkovic (University of Illinois at Urbana-Champaign), Ely Porat (Bar-Ilan University)IMA Annual Program Year Workshop
Network Links: Connecting Social, Communication, and Biological Network Analysis
February 27 - March 2, 2012
Organizers: Mathieu Blanchette (McGill University), Graham Cormode (AT&T Laboratories - Research), Natasha Przulj (Imperial College London), Ben J. Raphael (Brown University), S. Cenk Sahinalp (Simon Fraser University), Eric van den Berg (Telcordia)
Schedule
Wednesday, February 1
| 8:30am-9:00am | Coffee | Keller Hall 3-176 | SW1.30-2.1.12 | |
| 9:00am-10:00am | The Milnor Conjectures and Quadratic Forms | Parimala Raman (Emory University) | Keller Hall 3-180 | SW1.30-2.1.12 |
| 10:00am-10:30am | Coffee break | Keller Hall 3-176 | SW1.30-2.1.12 | |
| 10:30am-11:30am | A solution to the Arf-Kervaire invariant problem | Douglas Conner Ravenel (University of Rochester) | Keller Hall 3-180 | SW1.30-2.1.12 |
| 11:30am-11:40am | Break | SW1.30-2.1.12 | ||
| 11:40am-12:40pm | On the homology of Lie groups made discrete | Fabien Morel (Ludwig-Maximilians-Universität München) | Keller Hall 3-180 | SW1.30-2.1.12 |
| 12:40pm-1:00pm | Closing remarks | Keller Hall 3-180 | SW1.30-2.1.12 | |
| 2:30pm-3:00pm | Coffee break | Lind Hall 400 |
Thursday, February 2
| 2:30pm-3:00pm | Coffee break | Lind Hall 400 | ||
| 3:00pm-4:00pm | Computational Knot Theory with KnotPlot | Robert Glenn Scharein (Hypnagogic Software) | Lind Hall 305 | PS |
Friday, February 3
| 2:30pm-3:00pm | Coffee break | Lind Hall 400 |
Monday, February 6
| 2:30pm-3:00pm | Coffee break | Lind Hall 400 |
Tuesday, February 7
| 2:30pm-3:00pm | Coffee break | Lind Hall 400 | ||
| 3:00pm-4:00pm | TBD | Arthur Szlam (University of Minnesota) | Lind Hall 305 | PS |
Wednesday, February 8
| 2:30pm-3:00pm | Coffee break | Lind Hall 400 |
Thursday, February 9
| 2:30pm-3:00pm | Coffee break | Lind Hall 400 |
Friday, February 10
| 2:30pm-3:00pm | Coffee break | Lind Hall 400 |
Monday, February 13
| 9:00am-9:45am | Coffee and Registration | Keller Hall 3-176 | W2.13-17.12 | |
| 9:45am-10:00am | Welcome and Introduction | Keller Hall 3-180 | W2.13-17.12 | |
| 10:00am-11:00am | Tutorial: Cost effective sequencing of rare genetic variations | Yaniv Erlich (Whitehead Institute for Biomedical Research) | Keller Hall 3-180 | W2.13-17.12 |
| 11:00am-11:15am | Break | Keller Hall 3-176 | W2.13-17.12 | |
| 11:15am-12:15pm | Tutorial: Sparse signal recovery | Anna Gilbert (AT&T Laboratories - Research) | Keller Hall 3-180 | W2.13-17.12 |
| 12:15pm-2:00pm | Lunch | W2.13-17.12 | ||
| 2:00pm-3:00pm | Identification of rare alleles and their carriers using compressed se(que)nsing | Noam Shental (Open University of Israel) | Keller Hall 3-180 | W2.13-17.12 |
| 3:00pm-3:15pm | Break | Keller Hall 3-176 | W2.13-17.12 | |
| 3:15pm-3:45pm | Mining Rare Human Variations using Combinatorial Pooling | Dina Esposito (Whitehead Institute for Biomedical Research) | Keller Hall 3-180 | W2.13-17.12 |
| 3:45pm-4:15pm | RNA Structure Characterization from High-Throughput Chemical Mapping Experiments | Sharon Aviran (University of California, Berkeley) | Keller Hall 3-180 | W2.13-17.12 |
| 4:15pm-4:30pm | Break | Keller Hall 3-176 | W2.13-17.12 | |
| 4:30pm-5:30pm | RUMP session | Olgica Milenkovic (University of Illinois at Urbana-Champaign) | Keller Hall 3-180 | W2.13-17.12 |
| 6:30pm-8:00pm | Social Hour at the Campus Club 403 Coffman Memorial Union Map | Campus Club | W2.13-17.12 |
Tuesday, February 14
| 8:30am-9:00am | Coffee | Keller Hall 3-176 | W2.13-17.12 | |
| 9:00am-10:00am | Tutorial: Group Testing and Coding Theory | Atri Rudra (University at Buffalo (SUNY)) | Keller Hall 3-180 | W2.13-17.12 |
| 10:00am-10:15am | Group Photo | Keller Hall 3-180 | W2.13-17.12 | |
| 10:15am-11:15am | Network topology as a source of biological information | Natasha Przulj (Imperial College London) | Keller Hall 3-180 | W2.13-17.12 |
| 11:15am-11:30am | Break | Keller Hall 3-176 | W2.13-17.12 | |
| 11:30am-12:30pm | Superimposed Codes and Designs for Group Testing Models | Vyacheslav V. Rykov (University of Nebraska) | Keller Hall 3-180 | W2.13-17.12 |
| 12:30pm-2:00pm | Lunch | W2.13-17.12 | ||
| 2:00pm-3:00pm | Testing Boolean functions | Alex Samorodnitsky (Hebrew University) | Keller Hall 3-180 | W2.13-17.12 |
| 3:00pm-3:15pm | Coffee Break | Keller Hall 3-176 | W2.13-17.12 | |
| 3:15pm-3:45pm | Combinatorial Pooling Enables Selective Sequencing of the Barley Gene Space | Stefano Lonardi (University of California, Riverside) | Keller Hall 3-180 | W2.13-17.12 |
| 3:45pm-4:15pm | Superimposed codes | Zoltan Furedi (Hungarian Academy of Sciences (MTA)) | Keller Hall 3-180 | W2.13-17.12 |
| 4:15pm-5:30pm | Poster Session and Reception | Lind Hall 400 | W2.13-17.12 | |
| Poster - Finding one of m defective elements | Christian Deppe (Universität Bielefeld) | |||
| Poster - Upgraded Separate Testing of Inputs in Compressive Sensing | Mikhail B Malyutov (Northeastern University) |
Wednesday, February 15
| 8:30am-9:00am | Coffee | Keller Hall 3-176 | W2.13-17.12 | |
| 9:00am-10:00am | Shifted Transversal Design Smart-pooling: increasing sensitivity, specificity and efficiency in high-throughput biology | Nicolas Thierry-Mieg (Centre National de la Recherche Scientifique (CNRS)) | Keller Hall 3-180 | W2.13-17.12 |
| 10:00am-10:15am | Break | Keller Hall 3-176 | W2.13-17.12 | |
| 10:15am-11:15am | Weighted Pooling - Simple and Effective Techniques for Pooled High Throughput Sequencing Design | David Golan (Tel Aviv University) | Keller Hall 3-180 | W2.13-17.12 |
| 11:15am-11:30am | Break | Keller Hall 3-176 | W2.13-17.12 | |
| 11:30am-12:30pm | Genomic Privacy and the Limits of Individual Detection in a Pool | Sriram Sankararaman (Harvard Medical School) | Keller Hall 3-180 | W2.13-17.12 |
| 12:30pm-2:00pm | Lunch | W2.13-17.12 | ||
| 2:00pm-3:00pm | Superselectors: Efficient Constructions and Applications | Ferdinando Cicalese (Università di Salerno) | Keller Hall 3-180 | W2.13-17.12 |
| 3:00pm-3:15pm | Coffee Break | Keller Hall 3-176 | W2.13-17.12 | |
| 3:15pm-3:45pm | Probabilistic and combinatorial models for quantized group testing | Olgica Milenkovic (University of Illinois at Urbana-Champaign) | Keller Hall 3-180 | W2.13-17.12 |
| 3:45pm-4:15pm | Improved Constructions for Non-adaptive Threshold Group Testing | Mahdi Cheraghchi (Carnegie Mellon University) | Keller Hall 3-180 | W2.13-17.12 |
| 4:15pm-4:30pm | Break | W2.13-17.12 | ||
| 4:30pm-5:30pm | RUMP session | Yaniv Erlich (Whitehead Institute for Biomedical Research) | Keller Hall 3-180 | W2.13-17.12 |
Thursday, February 16
| 8:30am-9:00am | Coffee | Keller Hall 3-176 | W2.13-17.12 | |
| 9:00am-10:00am | Tutorial: The Data Stream Model | David P. Woodruff (IBM Research Division) | Keller Hall 3-180 | W2.13-17.12 |
| 10:00am-10:15am | Break | Keller Hall 3-176 | W2.13-17.12 | |
| 10:15am-11:15am | Sparser Johnson-Lindenstrauss Transforms | Jelani Nelson (Princeton University) | Keller Hall 3-180 | W2.13-17.12 |
| 11:15am-11:30am | Break | W2.13-17.12 | ||
| 11:30am-12:30pm | Length Reduction via Polynomials | Amihood Amir (Bar-Ilan University) | Keller Hall 3-180 | W2.13-17.12 |
| 12:30pm-2:00pm | Lunch | W2.13-17.12 | ||
| 2:00pm-3:00pm | Reconstruction of bacterial communities using sparse representation | Or Zuk (Broad Institute) | Keller Hall 3-180 | W2.13-17.12 |
| 3:00pm-3:15pm | Break | Keller Hall 3-176 | W2.13-17.12 | |
| 3:15pm-3:45pm | TBD | Mikhail B Malyutov (Northeastern University) | Keller Hall 3-180 | W2.13-17.12 |
| 3:45pm-4:15pm | A dynamic and quantitative protein interaction network regulating angiogenesis | Sylvie Ricard-Blum (Université Claude-Bernard (Lyon I)) | Keller Hall 3-180 | W2.13-17.12 |
| 4:15pm-4:30pm | Break | Keller Hall 3-176 | W2.13-17.12 | |
| 4:30pm-5:30pm | RUMP session | Ely Porat (Bar-Ilan University) | Keller Hall 3-180 | W2.13-17.12 |
Friday, February 17
| 8:30am-9:00am | Coffee | Keller Hall 3-176 | W2.13-17.12 | |
| 9:00am-10:00am | Streaming algorithms for approximating the length of the longest increasing subsequence | Anna Gal (University of Texas at Austin) | Keller Hall 3-180 | W2.13-17.12 |
| 10:00am-10:15am | Break | Keller Hall 3-176 | W2.13-17.12 | |
| 10:15am-11:15am | From screening clone libraries to detecting biological agents | Alexander Schliep (Rutgers University) | Keller Hall 3-180 | W2.13-17.12 |
| 11:15am-11:30am | Break | Keller Hall 3-176 | W2.13-17.12 | |
| 11:30am-12:30pm | A Group Testing Approach to Corruption Localizing Hashing | Annalisa De Bonis (Università di Salerno) | Keller Hall 3-180 | W2.13-17.12 |
Monday, February 20
| 2:30pm-3:00pm | Coffee break | Lind Hall 400 |
Tuesday, February 21
| 2:30pm-3:00pm | Coffee break | Lind Hall 400 |
Wednesday, February 22
| 2:30pm-3:00pm | Coffee break | Lind Hall 400 |
Thursday, February 23
| 2:30pm-3:00pm | Coffee break | Lind Hall 400 |
Friday, February 24
| 1:25pm-2:25pm | Computing the demagnetizing field in micromagnetics with periodic boundaries | Michael J. Donahue (National Institute of Standards and Technology) | Lind Hall 305 | IPS |
| 2:30pm-3:00pm | Coffee break | Lind Hall 400 |
Monday, February 27
Tuesday, February 28
Wednesday, February 29
| 2:30pm-3:00pm | Coffee break | Lind Hall 400 |
Thursday, March 1
| 2:30pm-3:00pm | Coffee break | Lind Hall 400 |
Friday, March 2
| 2:30pm-3:00pm | Coffee break | Lind Hall 400 |
Event Legend: |
|
| IPS | Industrial Problems Seminar |
| PS | IMA Postdoc Seminar |
| SW1.30-2.1.12 | Second Abel Conference: A Celebration of John Milnor |
| W2.13-17.12 | Group Testing Designs, Algorithms, and Applications to Biology |
Abstracts
| Amihood Amir (Bar-Ilan University) | Length Reduction via Polynomials |
| Abstract: Efficient handling of sparse data is a key challenge in Computer Science. Binary convolutions, such as the Fast Fourier Transform or theWalsh Transform are a useful tool in many applications and are efficiently solved.
In the last decade, several problems required efficient solution of sparse binary convolutions. Both randomized and deterministic algorithms were developed for efficiently computing the sparse FFT. The key operation in all these algorithms was length reduction. The sparse data is mapped into small vectors that preserve the convolution result. The reduction method used to-date was the modulo function since it preserves location (of the ”1” bits) up to cyclic shift. In this paper we present a new method for length reduction - polynomials. We show that this method allows a faster deterministic computation of the sparse FFT than currently known in the literature. It also enables the development of an efficient algorithm for computing the binary sparse Walsh Transform. To our knowledge, this is the first such algorithm in the literature. (Joint work with Oren Kappah, Ely Porat, and Amir Rothschild) |
|
| Sharon Aviran (University of California, Berkeley) | RNA Structure Characterization from High-Throughput Chemical Mapping Experiments |
| Abstract: New regulatory roles continue to emerge for both natural and engineered noncoding RNAs, many of which have specific secondary and tertiary structures essential to their function. This highlights a growing need to develop technologies that enable rapid and accurate characterization of structural features within complex RNA populations. Yet, available structure characterization techniques that are reliable are also vastly limited by technological constraints, while the accuracy of popular computational methods is generally poor. These limitations thus pose a major barrier to the comprehensive determination of structure from sequence and thereby to the development of mechanistic understanding of transcriptome dynamics. To address this need, we have recently developed a high-throughput structure characterization technique, called SHAPE-Seq, which simultaneously measures quantitative, single nucleotide-resolution, secondary and tertiary structural information for hundreds of RNA molecules of arbitrary sequence. SHAPE-Seq combines selective 2’-hydroxyl acylation analyzed by primer extension (SHAPE) chemical mapping with multiplexed paired-end deep sequencing of primer extension products. This generates millions of sequencing reads, which are then analyzed using a fully automated data analysis pipeline. Previous bioinformatics methods, in contrast, are laborious, heuristic, and expert-based, and thus prohibit high-throughput chemical mapping. In this talk, I will review recent developments in experimental RNA structure characterization as well as advances in sequencing technologies. I will then describe the SHAPE-Seq technique, focusing on its automated data analysis method, which relies on a novel probabilistic model of a SHAPE-Seq experiment, adjoined by a rigorous maximum likelihood estimation framework. I will demonstrate the accuracy and simplicity of our approach as well as its applicability to a general class of chemical mapping techniques and to more traditional SHAPE experiments that use capillary electrophoresis to identify and quantify primer extension products. This is joint work with Lior Pachter, Julius Lucks, Stefanie Mortimer, Shujun Luo, Cole Trapnell, Gary Schroth, Jennifer Doudna and Adam Arkin. |
|
| Mahdi Cheraghchi (Carnegie Mellon University) | Improved Constructions for Non-adaptive Threshold Group Testing |
| Abstract: The basic goal in combinatorial group testing is to identify a set of up to d defective items within a large population of size n >> d using a pooling strategy. Namely, the items can be grouped together in pools, and a single measurement would reveal whether there are one or more defectives in the pool. The threshold model is a generalization of this idea where a measurement returns positive if the number of defectives in the pool exceeds a fixed threshold u, negative if this number is below a fixed lower threshold L 0. | |
| Ferdinando Cicalese (Università di Salerno) | Superselectors: Efficient Constructions and Applications |
| Abstract: Superselectors subsume several important combinatorial structures used in the past few years to solve problems in group testing, compressed sensing, multi-channel conflict resolution and data security. We prove close upper and lower bounds on the size of superselectors and we provide efficient algorithms for their constructions. Albeit our bounds are very general, when they are instantiated on the combinatorial structures that are particular cases of superselectors (e.g., $(p,k,n)$-selectors cite{DGV}, $(d,ell)$-list-disjunct matrices, $MUT_k(r)$-families, $FUT(k, alpha)$-families, etc.) they match the best known bounds in terms of size of the structures (the relevant parameter in the applications). For appropriate values of parameters, our results also provide the first efficient deterministic algorithms for the construction of such structures. | |
| Annalisa De Bonis (Università di Salerno) | A Group Testing Approach to Corruption Localizing Hashing |
| Abstract: Efficient detection of integrity violations is crucial for the reliability of both data at rest and data in transit. In addition to detecting corruptions, it is often desirable to have the capability of obtaining information about the location of corrupted data blocks. While ideally one would want to always find all changes in the corrupted data, in practice this capability may be expensive, and one may be content with localizing or finding a superset of any changes. Corruption-localizing hashing is a cryptographic primitive that enhances collision-intractable hash functions thus improving the detection property of these functions into a suitable localization property. Besides allowing detection of changes in the input data, corruption-localizing hash schemes also obtain some superset of the changes location, where the accuracy of this superset with respect to the actual changes is a metric of special interest, called localization factor. In this talk we will address the problem of designing corruption-localizing hash schemes with reduced localization factor and with small time and storage complexity. We will show that this problem corresponds to a particular variant of nonadaptive group testing, and illustrate a construction technique based on superimposed codes. This group testing approach allowed to obtain corruption-localizing hash schemes that greatly improve on previous constructions. In particular, we will present a corruption-localizing hash scheme that achieves an arbitrarily small localization factor while only incurring a sublinear time and storage complexity. | |
| Christian Deppe (Universität Bielefeld) | Poster - Finding one of m defective elements |
| Abstract: In contrast to the classical goal of group testing we want to find onw defective elements of $D$ defective elements. We examine four different test functions. We give adaptive strategies and lower bounds for the number of tests. We treat the cases if the number of defectives are known and if the number of defectives are bounded. | |
| Michael J. Donahue (National Institute of Standards and Technology) | Computing the demagnetizing field in micromagnetics with periodic boundaries |
| Abstract: Micromagnetics is a classical model of magnetism in magnetic materials,
operative at the nanometer length scale. Typical micromagnetic
simulations model magnetic parts of dimensions ranging from tens of
nanometers up to a few micrometers. The most computationally expensive
portion of a micromagnetic simulation is the evaluation of the
long-range self-magnetostatic (aka dipole or demagnetizing) field. In
this talk I will provide some history of micromagnetics at NIST, and
discuss in detail some of the numerical and computational challenges
involved in a fast, accurate method for computing the demagnetizing
field in a simulation with periodic boundaries. Michael Donahue is a mathematician in the Applied and Computational Mathematics Division at the National Institute of Standards and Technology (NIST) in Gaithersburg, Maryland, where he does research on micromagnetics and leads development of the OOMMF public domain micromagnetics package. Prior to joining NIST, he was an industrial postdoctoral research associate at the IMA, working in conjunction with Siemens Corporate Research on artificial neural networks and computer vision. Dr. Donahue holds PhDs in mathematics and engineering from The Ohio State University, and has authored over 50 journal publications. |
|
| Yaniv Erlich (Whitehead Institute for Biomedical Research) | Tutorial: Cost effective sequencing of rare genetic variations |
| Abstract: In the past few years, we have experienced a paradigm shift in human genetics. Accumulating lines of evidence have highlighted the pivotal role of rare genetic variations in a wide variety of traits and diseases. Studying rare variations is a needle in a haystack problem, as large cohorts have to be assayed in order to trap the variations and gain statistical power. The performance of DNA sequencing is exponentially growing, providing sufficient capacity to profile an extensive number of specimens. However, sample preparation schemes do not scale as sequencing capacity. A brute force approach of preparing hundredths to thousands of specimens for sequencing is cumbersome and cost-prohibited. The next challenge, therefore, is to develop a scalable technique that circumvents the bottleneck in sample preparation. My tutorial will provide background on rare genetic variations and DNA sequencing. I will present our sample prep strategy, called DNA Sudoku, that utilizes combinatorial pooling/compressed sensing approach to find rare genetic variations. More importantly, I will discuss several major distinction from the classical combinatorial due to sequencing specific constraints. |
|
| Dina Esposito (Whitehead Institute for Biomedical Research) | Mining Rare Human Variations using Combinatorial Pooling |
| Abstract: Finding rare genetic variations in large cohorts requires tedious preparation of large numbers of specimens for sequencing. We are developing a solution, called DNA Sudoku, to reduce prep time and increase the throughput of samples. By using a combinatorial pooling approach, we multiplex specimens and then barcode the pools, rather than individuals, for sequencing in a single lane on the Illumina platform. We have developed a protocol for quantifying, calibrating, and pooling DNA samples using a liquid-handling robot, which has required a significant amount of testing in order to reduce volume variation. I will discuss our protocol and the steps we have taken to reduce CV. For accurate decoding and to reduce the possibility of specimen dropout, it is important that the DNA samples are accurately quantified and calibrated so that equal amounts can be pooled and sequenced. We can determine the number of carriers in each pool from sequencing output and reconstruct the original identity of individual specimens based on the pooling design, allowing us to identify a small number of carriers in a large cohort. |
|
| Zoltan Furedi (Hungarian Academy of Sciences (MTA)) | Superimposed codes |
| Abstract: There are many instances in Coding Theory when codewords must be restored from
partial information, like defected data (error correcting codes), or some superposition of the strings. These lead to superimposed codes, a close relative of group testing problems. There are lots of versions and related problems, like Sidon sets, sum-free sets, unionfree families, locally thin families, cover-free codes and families, etc. We discuss two cases cancellative and union-free codes. A family of sets Ƒ (and the corresponding code of 0-1 vectors) is called union-free if A ∪ B≠ C ∪ D and A,B,C,D ∈ F imply {A,B} = {C,D}. Ƒ is called t-cancellative if for all distict t + 2 members A1, … ,At and B,C ∈ Ƒ Let ct(n) be the size of the largest t-cancellative code on n elements. We significantly improve the previous upper bounds of Körner and Sinaimeri, e.g., we show c2(n) ≤ 20:322n (for n > n0). |
|
| Anna Gal (University of Texas at Austin) | Streaming algorithms for approximating the length of the longest increasing subsequence |
| Abstract: The data stream model allows only one way access to the data, possibly with several passes. This model is motivated by problems related to processing very large data sets, when it is desirable to keep only a small part of the data in active memory at any given point during the computation. I will talk about proving lower bounds on how much space (memory) is necessary to still be able to solve the given task. I will focus on the problem of approximating the length of the longest increasing subsequence, which is a measure of how well the data is sorted. Joint work with Parikshit Gopalan. |
|
| Anna Gilbert (AT&T Laboratories - Research) | Tutorial: Sparse signal recovery |
| Abstract: My talk will be a tutorial about sparse signal recovery but, more importantly, I will provide an overview of what the research problems are at the intersection of biological applications of group testing, streaming algorithms, sparse signal recovery, and coding theory. The talk should help set the stage for the rest of the workshop. | |
| David Golan (Tel Aviv University) | Weighted Pooling - Simple and Effective Techniques for Pooled High Throughput Sequencing Design |
| Abstract: Despite the rapid decrease in sequencing costs, sequencing a large group of individuals is still prohibitively expensive. Recently, several sophisticated pooling designs were suggested that can identify carriers of rare alleles in large cohorts with a significantly smaller number of lanes, thus dramatically reducing the cost of such large scale genotyping projects. These approaches all use combinatorial pooling designs where each individual is either present in a pool or absent from it. One can then infer the number of carriers in a pool, and by combining information across pools, reconstruct the identity of the carriers. We show that one can gain further efficiency and cost reduction by using “weighted” designs, in which different individuals donate different amounts of DNA to the pools. Intuitively, in this situation the number of mutant reads in a pool does not only indicate the number of carriers, but also of the identity of the carriers. We describe and study a simple but powerful example of such weighted designs, with non-overlapping pools. We demonstrate that even this naive approach is not only easier to implement and analyze but is also competitive in terms of accuracy with combinatorial designs when identifying very rare variants, and is superior to the combinatorial designs when genotyping more common variants. We then discuss how weighting can be further incorporated into existing designs to increase their accuracy and demonstrate the resulting improvement in reconstruction efficiency using simulations. Finally, we argue that these weighted designs have enough power to facilitate detection of common alleles, so they can be used as a cornerstone of whole-exome or even whole-genome sequencing projects. |
|
| Stefano Lonardi (University of California, Riverside) | Combinatorial Pooling Enables Selective Sequencing of the Barley Gene Space |
| Abstract: We propose a new sequencing protocol that combines recent advances in
combinatorial pooling design and second-generation sequencing
technology to efficiently approach de novo selective genome
sequencing. We show that combinatorial pooling is a cost-effective
and practical alternative to exhaustive DNA barcoding when dealing
with hundreds or thousands of DNA samples, such as genome-tiling
gene-rich BAC clones. The novelty of the protocol hinges on the
computational ability to efficiently compare hundreds of million of
short reads and assign them to the correct BAC clones so that the
assembly can be carried out clone-by-clone. Experimental results on
simulated data for the rice genome show that the deconvolution is
extremely accurate (99.57% of the deconvoluted reads are assigned to
the correct BAC), and the resulting BAC assemblies have very high
quality (BACs are covered by contigs over about 77% of their length,
on average). Experimental results on real data for a gene-rich subset of
the barley genome confirm that the deconvolution is accurate (almost
70% of left/right pairs in paired-end reads are assigned to the same
BAC, despite being processed independently) and the BAC assemblies have
good quality (the average sum of all assembled contigs is about 88%
of the estimated BAC length). Joint work with D. Duma (UCR), M. Alpert (UCR), F. Cordero (U of Torino), M. Beccuti (U of Torino), P. R. Bhat (UCR and Monsanto), Y. Wu (UCR and Google), G. Ciardo (UCR), B. Alsaihati (UCR), Y. Ma (UCR), S. Wanamaker (UCR), J. Resnik (UCR), and T. J. Close (UCR). Preprint available at http://arxiv.org/abs/1112.4438 |
|
| Mikhail B Malyutov (Northeastern University) | Poster - Upgraded Separate Testing of Inputs in Compressive Sensing |
| Abstract: Screening experiments (SE) deal with finding a small number s Active Inputs (AIs) out of a vast total amount t of inputs in a regressionmodel. Of special interest in the SE theory is finding the so-called maximal rate (capacity). For a set of t elements, denote the set of its s-subsets by (s, t). Introduce a noisy system with t binary inputs and one output y. Suppose that only s 0. The f-capacity Cf (s) = limt!1(log t/Nf (s, t, )) for any > 0 is the ‘limit for the per- formance of the f-analysis’. We obtained tight capacity bounds [4], [5] by formalizing CSS as a special case of Multi-Access Communication Channels (MAC) of information transmission capacity region construction developed by R. Ahlswede in [1] and comparing CSS’ maximal rate (capacity) with small error for two practical methods of outputs’ analysis under the optimal CSS design motivated by applications like [2] . Recovering Active Inputs with small error probability and accurate parameter estimation are both possible with rates less than capacity and impossible with larger rates. A staggering amount of attention was recently devoted to the study of compressive sensing and related areas using sparse priors in over parameterized linear models which may be viewed as a special case of our models with continuous input levels. The threshold phenomenon was empirically observed in early papers [3], [6] : as the dimension of a randominstance of a problem grows there is a sharp transition from successful recovery to failure as a function of the number of observations versus the dimension and sparsity of the unknown signal. Finding this threshold is closely related to our capacity evaluation. Some threshold bounds for the compressive sensing were made using standard information-theoretic tools, e.g. in [15] | |
| Olgica Milenkovic (University of Illinois at Urbana-Champaign) | Probabilistic and combinatorial models for quantized group testing |
| Abstract: We consider a novel group testing framework where defectives obey a probabilistic model in which the number and set of defectives is governed by a graphical model. We furthermore assume that the defectives have importance factors that influence their strength on the test outcomes and the accuracy with which the outcomes are read. This kind of scenario arises, for example, in MAC channels with networked users using different communication powers, or in DNA pooling schemes which involve large families. | |
| Fabien Morel (Ludwig-Maximilians-Universität München) | On the homology of Lie groups made discrete |
| Abstract: In this talk I will recall and discuss the conjecture of John Milnor on the homology of Lie groups made discrete, as well as its algebraic analogue, the Friedlander conjecture. In a work still partially in progress, we give a proof of that conjecture for algebraic groups G over algebraically closed fields. I will sketch some ideas behind this proof, in particular the role of A1-homotopy theory (already used by V. Voevodsky to prove other conjectures of John Milnor concerning mod 2 Galois cohomology and quadratic forms) and the role of a new object attached to G, its simplicial building. We will emphasize the case G = SL_2, SL_3,... |
|
| Jelani Nelson (Princeton University) | Sparser Johnson-Lindenstrauss Transforms |
| Abstract: The Johnson-Lindenstrauss (JL) lemma (1984) states that any n points
in d-dimensional Euclidean space can be embedded into k = O((log
n)/eps^2) dimensions so that all pairwise distances are preserved up
to 1+/-eps. Furthermore, this embedding can be achieved via a linear
mapping. The JL lemma is a useful tool for speeding up solutions to
several high-dimensional problems: closest pair, nearest neighbor,
diameter, minimum spanning tree, etc. It also speeds up some
clustering and string processing algorithms, reduces the amount of
storage required to store a dataset, and can be used to reduce memory
required for numerical linear algebra problems such as linear
regression and low rank approximation. The original proofs of the JL lemma let the linear mapping be specified by a random dense k x d matrix (e.g. i.i.d. Gaussian entries). Thus, performing an embedding requires dense matrix-vector multiplication. We give the first construction of linear mappings for JL in which only a subconstant fraction of the embedding matrix is non-zero, regardless of how eps and n are related, thus always speeding up the embedding time. Previous constructions only achieved sparse embedding matrices for 1/eps >> log n. This is joint work with Daniel Kane (Stanford). |
|
| Natasha Przulj (Imperial College London) | Network topology as a source of biological information |
| Abstract: Sequence-based computational approaches have revolutionized biological understanding. However, they can fail to explain some biological phenomena. Since proteins aggregate to perform a function instead of acting in isolation, the connectivity of a protein interaction network (PIN) will provide additional insight into the inner working on the cell, over and above sequences of individual proteins. We argue that sequence and network topology give insights into complementary slices of biological information, which sometimes corroborate each other, but sometimes do not. Hence, the advancement depends on the development of sophisticated graph-theoretic methods for extracting biological knowledge purely from network topology before being integrated with other types of biological data (e.g., sequence). However, dealing with large networks is non-trivial, since many graph-theoretic problems are computationally intractable, so heuristic algorithms are sought. Analogous to sequence alignments, alignments of biological networks will likely impact biomedical understanding. We introduce a family of topology-based network alignment (NA) algorithms, (that we call GRAAL algorithms), that produces by far the most complete alignments of biological networks to date: our alignment of yeast and human PINs demonstrates that even distant species share a surprising amount of PIN topology. We show that both species phylogeny and protein function can be extracted from our topological NA. Furtermore, we demonstrate that the NA quality improves with integration of additional data sources (including sequence) into the alignment algorithm: surprisingly, 77.7% of proteins in the baker’s yeast PIN participate in a connected subnetwork that is fully contained in the human PIN suggesting broad similarities in internal cellular wiring across all life on Earth. Also, we demonstrate that topology around cancer and non-cancer genes is different and when integrated with functional genomics data, it successfully predicts new cancer genes in melanogenesis-related pathways. |
|
| Parimala Raman (Emory University) | The Milnor Conjectures and Quadratic Forms |
| Abstract: The Milnor conjectures relating the graded Witt ring and the mod-2 Galois cohomology ring of a field have been a driving force in the algebraic theory of quadratic forms. The degree 2 norm residue isomorphism, due to Merkurjev, established the first case of the Milnor conjectures and ushered in a new era in the theory of quadratic forms. We shall explain some of the consequences of the Milnor conjectures, with particular reference to invariants of fields associated to quadratic forms. | |
| Douglas Conner Ravenel (University of Rochester) | A solution to the Arf-Kervaire invariant problem |
| Abstract: The 1963 work of Kervaire-Milnor on the classification of exotic spheres in terms of the stable homotopy groups of spheres left one unanswered question in dimensions congruent to two modulo four. Subsequent work by Brown-Peterson and Browder gave the answer in all dimensions that are not two less than a power of two. We solve the problem in all remaining cases except 126. Our answer is the opposite of the one that many sought in the 1970s. | |
| Sylvie Ricard-Blum (Université Claude-Bernard (Lyon I)) | A dynamic and quantitative protein interaction network regulating angiogenesis |
| Abstract: Angiogenesis, consisting in the formation of blood vessels from preexisting ones, is of crucial importance in pathological situations such as cancer and diabetes and is a therapeutic target for these two diseases. We have developed protein and sugar arrays probed by surface plasmon resonance (SPR) imaging to identify binding partners of proteins, polysaccharides and receptors regulating angiogenesis. Interactions collected from our own experiments and from literature curation have been used to build a network comprising protein-protein and protein-polysaccharide interactions. To switch from a static to a dynamic and quantitative interaction network, we have measured kinetics and affinity of interactions by SPR to discriminate transient from stable interactions and to prioritize interactions in the network. We have also identified protein interaction sites either experimentally or by molecular modeling to discriminate interactions occurring simultaneously from those taking place sequentially. The ultimate step is to integrate, using bioinformatics tools, all these parameters in the interaction network together with inhibitors of these interactions and with gene and protein expression data available from Array Express or Gene Expression Omnibus and from the Human Protein Atlas. This dynamic network will allow us to understand how angiogenesis is regulated in a concerted fashion via several receptors and signaling pathways, to identify crucial interactions for the integrity of the network that are potential therapeutic targets, and to predict the side effects of anti-angiogenic treatments. | |
| Atri Rudra (University at Buffalo (SUNY)) | Tutorial: Group Testing and Coding Theory |
| Abstract: Group testing was formalized by Dorfman in his 1943 paper and was originally used in WW-II to identify soldiers with syphilis. The main insight in this application is that blood samples from different soldiers can be combined to check if at least one of soldiers in the pool has the disease. Since then group testing has found numerous applications in many areas such as (computational) biology, combinatorics and (theoretical) computer science. Theory of error-correcting codes, or coding theory, was born in the works of Shannon in 1948 and Hamming in 1950. Codes are ubiquitous in our daily life and have also found numerous applications in theoretical computer science in general and computational complexity in particular. Kautz and Singleton connected these two areas in their 1964 paper by using "code concatenation" to design good group testing schemes. All of the (asymptotically) best know explicit constructions of group testing schemes use the code concatenation paradigm. In this talk, we will focus on the "decoding" problem for group testing: i.e. given the outcomes of the tests on the pools, identify the infected soldiers. Recent applications of group testing in data stream algorithm require sub-linear time decoding, which is not guaranteed by the traditional constructions. The talk will first survey the Kautz-Singleton construction and then will will show how recent developments in list decoding of codes lead in a modular way to sub-linear time decodable group testing schemes. |
|
| Vyacheslav V. Rykov (University of Nebraska) | Superimposed Codes and Designs for Group Testing Models |
| Abstract: We will discuss superimposed codes and non-adaptive group testing designs arising from the potentialities of compressed genotyping models in molecular biology. The given survey is also motivated by the 30th anniversary of our recurrent upper bound on the rate of superimposed codes published in 1982. | |
| Alex Samorodnitsky (Hebrew University) | Testing Boolean functions |
| Abstract: I will talk about property testing of Boolean functions, concentrating on two topics: testing monotonicity (an example of a combinatorial property) and testing the property of being a low-degree polynomial (an algebraic property). | |
| Sriram Sankararaman (Harvard Medical School) | Genomic Privacy and the Limits of Individual Detection in a Pool |
| Abstract: Statistical power to detect associations in genome-wide association studies can be enhanced by combining data across studies in meta-analysis or replication studies. Such methods require data to flow freely in the scientific community, however, and this raises privacy concerns. Till recently, many studies pooled individuals together, making only the allele frequencies of each SNP in the pool publicly available. However a technique that could be used to detect the presence of individual genotypes from such data prompted organizations such as the NIH to restrict public access to summary data . To again allow public access to data from association studies, we need to determine which set of SNPs can be safely exposed while preserving an acceptable level of privacy. To answer this question, we provide an upper bound on the power achievable by any detection method as a function of factors such as the number and the allele frequencies of exposed SNPs, the number of individuals in the pool, and the false positive rate of the method. Our approach is based on casting the problem in a statistical hypothesis testing framework for which the likelihood ratio test (LR-test) attains the maximal power achievable. Our analysis provides quantitative guidelines for researchers to make SNPs public without compromising privacy. We recommend, based on our analysis, that only common independent SNPs be exposed. The final decision regarding the exposed SNPs should be based on the analytical bound in conjunction with empirical estimates of the power of the LR test. To this end, we have implemented a tool, SecureGenome, that determines the set of SNPs that can be safely exposed for a given dataset. |
|
| Robert Glenn Scharein (Hypnagogic Software) | Computational Knot Theory with KnotPlot |
| Abstract: Mathematical knot theory is an exciting branch of topology that is relevant to physics, chemistry and biology. After a brief introduction to knot theory, we will explore several applications where computational methods play a useful role. When experimenting with knots on a computer, it is helpful to have powerful tools for the creation of initial conformations, for performing simulations on those conformations and also to compute topological and geometric properties of any resulting products. One such tool is the software KnotPlot, developed by the speaker over a period of many years. KnotPlot permits a wide range of interesting experiments to be performed. Several of these will be discussed, one important area being the tangling and untangling of DNA. Finally, we will dip into the more esoteric realm of higher dimensional knotting. | |
| Alexander Schliep (Rutgers University) | From screening clone libraries to detecting biological agents |
| Abstract: Group testing has made many contributions to modern molecular biology.
In the Human Genome Project large clone libraries where created
to amplify DNA. Widely used group testing schemes vastly accelerated
the detection of overlaps between the individual clones in these libraries through experiments, realizing savings both in effort and materials. Modern molecular biology also contributed to group testing. The problem of generalized group testing (in the combinatorial sense) arises naturally, when one uses oligonucleotide probes to identify biological agents present in a sample. In this setting a group testing design cannot be chosen arbitrarily. The possible columns of a group testing design matrix are prescribed by the biology, namely by the hybridization reactions between target DNA and probes |
|
| Noam Shental (Open University of Israel) | Identification of rare alleles and their carriers using compressed se(que)nsing |
| Abstract: Identification of rare variants by resequencing is important both for detecting novel variations and for screening individuals for known disease alleles. New technologies enable low-cost resequencing of target regions, although it is still prohibitive to test more than a few individuals. We propose a novel pooling design that enables the recovery of novel or known rare alleles and their carriers in groups of individuals. The method is based on combining next-generation sequencing technology with a Compressed Sensing (CS) approach. The approach is general, simple and efficient, allowing for simultaneous identification of multiple variants and their carriers.
It reduces experimental costs, i.e., both sample preparation related costs and direct sequencing costs, by up to 70 fold, and thus allowing to scan much larger cohorts.
We demonstrate the performance of our approach over several publicly available data sets, including the 1000 Genomes Pilot 3 study.
We believe our approach may significantly improve cost effectiveness of future association studies, and in screening large DNA cohorts for specific risk alleles. We will present initial results of two projects that were initiated following publication. The first project concerns identification of de novo SNPs in genetic disorders common among Ashkenazi Jews, based on sequencing 3000 DNA samples. The second project in plant genetics involves identifying SNPs related to water and silica homeostasis in Sorghum bicolor, based on sequencing 3000 DNA samples using 1-2 Illumina lanes. Joint work with Amnon Amir from the Weizmann Institute of Science, and Or Zuk from the Broad Institute of MIT and Harvard |
|
| Nicolas Thierry-Mieg (Centre National de la Recherche Scientifique (CNRS)) | Shifted Transversal Design Smart-pooling: increasing sensitivity, specificity and efficiency in high-throughput biology |
| Abstract: Group testing, also know as smart-pooling, is a promising strategy for achieving high efficiency, sensitivity, and specificity in systems-level projects. It consists in assaying well-chosen pools of probes, such that each probe is present in several pools, hence tested several times. The goal is to construct the pools so that the positive probes can usually be directly identified from the pattern of positive pools, despite the occurrence of false positives and false negatives. While striving for this goal, two interesting mathematical or computational problems emerge: the pooling problem (how should the pools be designed?), and the decoding problem (how to interpret the outcomes?). In this talk I will discuss these questions and the solutions we have proposed: a flexible and powerful combinatorial construction for designing smart-pools (the Shifted Transveral Design, STD), and an efficient exact algorithm for interpreting results (interpool). I will then present the results of validation experiments that we have performed in the context of yeast two-hybrid interactome mapping. | |
| David P. Woodruff (IBM Research Division) | Tutorial: The Data Stream Model |
| Abstract: The data stream model has emerged as a way of analyzing algorithmic efficiency in the presence of massive data sets. Typically the algorithm is allowed a few (usually one) passes over the input, and must use limited memory and have very fast per input item processing time. I will give a survey of algorithms and lower bounds in this area, with an emphasis on problems such as norm estimation, numerical linear algebra, empirical entropy, l_p-sampling, and heavy hitters. Time-permitting I'll also discuss the extension to functional monitoring, in which there are multiple sites each with a data stream and a central coordinator should continuously maintain a statistic over the union of the data streams. | |
| Or Zuk (Broad Institute) | Reconstruction of bacterial communities using sparse representation |
| Abstract: Determining the identities and frequencies of species present in a sample is a central problem in metagenomics, with scientific, environmental and clinical implications. A popular approach to the problem is sequencing the Ribosomal 16s RNA gene in the sample using universal primers, and using variation in the gene's sequence between different species to identify the species present in the sample. We present a novel framework for community reconstruction, based on sparse representation; while millions of microorganisms are present on earth, with known 16s sequences stored in a database, only a small minority (typically a few hundreds) are likely to be present in any given sample, We discuss the statistical framework, algorithms used and results in terms of accuracy and species resolution. |
|
Visitors in Residence
| Alejandro Adem | University of British Columbia | 1/29/2012 - 2/1/2012 |
| Anar Akhmedov | University of Minnesota | 1/30/2012 - 2/1/2012 |
| Zack W Almquist | University of California, Irvine | 2/26/2012 - 3/2/2012 |
| Brendan P.W. Ames | University of Minnesota | 8/31/2011 - 8/30/2012 |
| Amihood Amir | Bar-Ilan University | 2/12/2012 - 2/16/2012 |
| John David Arellano | Rice University | 2/25/2012 - 3/2/2012 |
| Amir Asiaee Taheri | University of Minnesota | 2/27/2012 - 3/2/2012 |
| Sharon Aviran | University of California, Berkeley | 2/12/2012 - 2/15/2012 |
| Gary Bader | University of Toronto | 2/26/2012 - 3/1/2012 |
| Joel S Bader | Johns Hopkins University | 2/26/2012 - 3/2/2012 |
| Arindam Banerjee | University of Minnesota | 9/1/2011 - 6/30/2012 |
| Alexander Barg | University of Maryland | 2/12/2012 - 2/16/2012 |
| Hyman Bass | University of Michigan | 1/29/2012 - 2/1/2012 |
| Maria Basterra | University of New Hampshire | 1/29/2012 - 2/1/2012 |
| Jeremy Bellay | University of Maryland | 2/26/2012 - 3/2/2012 |
| Tanya Berger-Wolf | University of Illinois at Chicago | 2/26/2012 - 3/2/2012 |
| Julie Bergner | University of California, Riverside | 1/29/2012 - 2/1/2012 |
| Andrew John Beveridge | Macalester College | 9/1/2011 - 5/15/2012 |
| Smriti Bhagat | Technicolor Inc. | 2/27/2012 - 2/29/2012 |
| Manisha Bhardwaj | University of Houston | 2/26/2012 - 3/2/2012 |
| Jodi Black | Bucknell University | 1/29/2012 - 2/1/2012 |
| Mathieu Blanchette | McGill University | 2/26/2012 - 3/3/2012 |
| Sergey G Bobkov | University of Minnesota | 9/1/2011 - 6/30/2012 |
| Shyam Boriah | University of Minnesota | 2/27/2012 - 3/2/2012 |
| William Browder | Princeton University | 1/29/2012 - 2/1/2012 |
| Yiqing Cai | University of Pennsylvania | 2/26/2012 - 3/2/2012 |
| Luca Capogna | University of Minnesota | 8/15/2011 - 6/10/2012 |
| Sylvain Edward Cappell | New York University | 1/29/2012 - 2/1/2012 |
| Aycil Cesmelioglu | University of Minnesota | 9/30/2010 - 8/30/2012 |
| Huilan Chang | National University of Kaohsiung | 2/12/2012 - 2/17/2012 |
| Mahdi Cheraghchi | Carnegie Mellon University | 2/12/2012 - 2/17/2012 |
| Mung Chiang | Princeton University | 2/27/2012 - 3/2/2012 |
| Sou-Cheng Choi | Argonne National Laboratory | 2/12/2012 - 2/16/2012 |
| Ferdinando Cicalese | Università di Salerno | 2/11/2012 - 2/16/2012 |
| Ionut Ciocan-Fontanine | University of Minnesota | 1/31/2012 - 2/1/2012 |
| Barry Cipra | NONE | 1/30/2012 - 2/1/2012 |
| Paolo Codenotti | University of Minnesota | 9/1/2011 - 8/30/2012 |
| Frederick R. Cohen | University of Rochester | 1/29/2012 - 2/1/2012 |
| Graham Cormode | AT&T Laboratories - Research | 2/27/2012 - 3/2/2012 |
| Lenore J. Cowen | Tufts University | 2/26/2012 - 3/2/2012 |
| Mark Crovella | Boston University | 2/26/2012 - 3/2/2012 |
| Jintao Cui | University of Minnesota | 8/31/2010 - 8/30/2012 |
| Xiaoyi Cui | University of Minnesota | 1/30/2012 - 2/1/2012 |
| Phuong Dao | Simon Fraser University | 2/26/2012 - 3/2/2012 |
| Isabel K. Darcy | University of Iowa | 9/1/2011 - 6/30/2012 |
| Ingrid Daubechies | Duke University | 2/12/2012 - 2/17/2012 |
| James F Davis | Indiana University | 1/29/2012 - 2/1/2012 |
| Annalisa De Bonis | Università di Salerno | 2/12/2012 - 2/17/2012 |
| Christian Deppe | Universität Bielefeld | 2/12/2012 - 2/18/2012 |
| Raamesh Deshpande | University of Minnesota | 2/27/2012 - 3/2/2012 |
| Michael J. Donahue | National Institute of Standards and Technology | 2/23/2012 - 2/24/2012 |
| Ding-Zhu Du | University of Texas | 2/12/2012 - 2/15/2012 |
| William G. Dwyer | University of Notre Dame | 1/29/2012 - 2/2/2012 |
| Robert Edwards | University of California, Los Angeles | 1/30/2012 - 2/1/2012 |
| Geir Ellingsrud | University of Oslo | 1/29/2012 - 2/1/2012 |
| Amin Emad | University of Illinois at Urbana-Champaign | 2/12/2012 - 2/17/2012 |
| Yaniv Erlich | Whitehead Institute for Biomedical Research | 2/12/2012 - 2/17/2012 |
| Leonardo Espin | NONE | 9/1/2011 - 6/30/2012 |
| Dina Esposito | Whitehead Institute for Biomedical Research | 2/12/2012 - 2/17/2012 |
| Pedro Andres Forero | University of Minnesota | 2/27/2012 - 3/2/2012 |
| John Fornaess | University of Michigan | 1/28/2012 - 2/1/2012 |
| Zoltan Furedi | Hungarian Academy of Sciences (MTA) | 2/12/2012 - 2/17/2012 |
| Anna Gal | University of Texas at Austin | 2/12/2012 - 2/17/2012 |
| Tingran Gao | Duke University | 1/29/2012 - 2/1/2012 |
| Carlos Andres Garavito-Garzon | University of Minnesota | 9/8/2011 - 6/30/2012 |
| Nikolaos Gatsis | University of Minnesota | 2/27/2012 - 3/2/2012 |
| Hillel H. Gershenson | NONE | 1/30/2012 - 2/1/2012 |
| Lise Getoor | University of Maryland | 2/26/2012 - 3/1/2012 |
| Georgios B Giannakis | University of Minnesota | 2/27/2012 - 3/2/2012 |
| Anna Gilbert | AT&T Laboratories - Research | 2/12/2012 - 2/17/2012 |
| Samuel Gitler | CINVESTAV | 1/29/2012 - 2/1/2012 |
| David Golan | Tel Aviv University | 2/12/2012 - 2/17/2012 |
| Manuel Gomez Rodriguez | Max-Planck-Institut für Intelligente Systeme | 2/26/2012 - 3/3/2012 |
| Robert Gulliver | University of Minnesota | 1/30/2012 - 2/1/2012 |
| Ian Hambleton | McMaster University | 1/29/2012 - 2/1/2012 |
| Michael Hill | University of Virginia | 1/29/2012 - 2/1/2012 |
| Shawndra Hill | University of Pennsylvania | 2/26/2012 - 3/1/2012 |
| Michael J. Hopkins | Harvard University | 1/28/2012 - 2/1/2012 |
| Yulia Hristova | University of Minnesota | 9/1/2010 - 8/31/2012 |
| Miriam Huntley | Harvard University | 1/30/2012 - 2/1/2012 |
| Dale Husemoller | Max Planck Institute for Mathematics | 1/29/2012 - 2/1/2012 |
| Ali Jadbabaie | University of Pennsylvania | 2/29/2012 - 3/2/2012 |
| Bjørn Jahren | University of Oslo | 1/29/2012 - 2/2/2012 |
| Vuk Janjic | Imperial College London | 2/26/2012 - 3/2/2012 |
| Dihua Jiang | University of Minnesota | 1/30/2012 - 2/1/2012 |
| Niles Johnson | University of Georgia | 1/29/2012 - 2/1/2012 |
| Igor Jurisica | University of Toronto | 2/26/2012 - 3/2/2012 |
| Donald Kahn | University of Minnesota | 1/30/2012 - 2/1/2012 |
| Jaya Kawale | University of Minnesota | 2/27/2012 - 3/2/2012 |
| Hee Jung Kim | Pohang University of Science and Technology (POSTECH) | 1/29/2012 - 2/1/2012 |
| Carl Kingsford | University of Maryland | 2/26/2012 - 3/2/2012 |
| Robion Kirby | University of California, Berkeley | 1/29/2012 - 2/1/2012 |
| Elizabeth Koch | University of Minnesota | 2/27/2012 - 3/2/2012 |
| Eric Kolaczyk | Boston University | 2/26/2012 - 2/29/2012 |
| Mehmet Koyuturk | Case Western Reserve University | 2/28/2012 - 3/2/2012 |
| Ravi Kumar | Yahoo! Inc. | 2/27/2012 - 3/2/2012 |
| Kee Yuen Lam | University of British Columbia | 1/29/2012 - 2/1/2012 |
| Tsit Yuen Lam | University of California, Berkeley | 1/29/2012 - 2/1/2012 |
| Tyler Lawson | University of Minnesota | 1/30/2012 - 2/1/2012 |
| Young-Ju Lee | Rutgers University | 2/19/2012 - 2/21/2012 |
| Gilad Lerman | University of Minnesota | 9/1/2011 - 6/30/2012 |
| Jure Leskovec | Stanford University | 2/29/2012 - 3/2/2012 |
| Lizao Li | University of Minnesota | 1/30/2012 - 2/1/2012 |
| Tian-Jun Li | University of Minnesota | 1/30/2012 - 2/1/2012 |
| Tong Li | University of Iowa | 2/26/2012 - 3/3/2012 |
| Wenbo Li | University of Delaware | 9/1/2011 - 5/30/2012 |
| David Liben-Nowell | Carleton College | 2/27/2012 - 3/2/2012 |
| Lek-Heng Lim | University of Chicago | 2/1/2012 - 6/10/2012 |
| Ayelet Lindenstrauss | Indiana University | 1/29/2012 - 2/1/2012 |
| Xin Liu | University of Minnesota | 8/31/2011 - 8/30/2012 |
| Stefano Lonardi | University of California, Riverside | 2/12/2012 - 2/16/2012 |
| Ying Lu | University of Minnesota | 2/27/2012 - 3/2/2012 |
| Tom Lyche | University of Oslo | 1/29/2012 - 2/1/2012 |
| Shiqian Ma | University of Minnesota | 8/31/2011 - 8/30/2013 |
| Ib Madsen | University of Copenhagen | 1/29/2012 - 2/1/2012 |
| Mikhail B Malyutov | Northeastern University | 2/12/2012 - 2/18/2012 |
| Yi Mao | Michigan State University | 2/12/2012 - 2/17/2012 |
| Yu (David) Mao | University of Minnesota | 8/31/2010 - 8/30/2012 |
| Albert Marden | University of Minnesota | 1/30/2012 - 2/1/2012 |
| Athina Markopoulou | University of California, Irvine | 2/26/2012 - 3/2/2012 |
| Gabriela Martínez | University of Minnesota | 8/31/2011 - 8/30/2013 |
| John McCleary | Vassar College | 1/29/2012 - 2/2/2012 |
| Dusa McDuff | Barnard College | 1/27/2012 - 2/2/2012 |
| Danielle Paola Mersch | Université de Lausanne | 2/25/2012 - 3/3/2012 |
| William Messing | University of Minnesota | 1/30/2012 - 2/1/2012 |
| Olgica Milenkovic | University of Illinois at Urbana-Champaign | 2/12/2012 - 2/18/2012 |
| Tijana Milenkovic | University of Notre Dame | 2/26/2012 - 3/2/2012 |
| John Milnor | SUNY | 1/27/2012 - 2/2/2012 |
| Tom Milnor | University of British Columbia | 1/27/2012 - 2/1/2012 |
| Dimitrios Mitsotakis | University of Minnesota | 10/27/2010 - 8/31/2012 |
| Jack Morava | Johns Hopkins University | 1/29/2012 - 2/2/2012 |
| Fabien Morel | Ludwig-Maximilians-Universität München | 1/28/2012 - 2/2/2012 |
| Chad Myers | University of Minnesota | 2/27/2012 - 3/2/2012 |
| Jelani Nelson | Princeton University | 2/12/2012 - 2/17/2012 |
| Jennifer Neville | Purdue University | 2/26/2012 - 3/2/2012 |
| Hung Ngo | University at Buffalo (SUNY) | 2/12/2012 - 2/17/2012 |
| Peter J. Olver | University of Minnesota | 1/30/2012 - 2/1/2012 |
| Kent Orr | Indiana University | 1/29/2012 - 2/1/2012 |
| Peter Ozsvath | Massachusetts Institute of Technology | 1/29/2012 - 2/1/2012 |
| Mary Therese Padberg | University of Iowa | 2/12/2012 - 2/17/2012 |
| Aditya Pal | University of Minnesota | 2/26/2012 - 3/2/2012 |
| Hyungju Park | Pohang University of Science and Technology (POSTECH) | 1/29/2012 - 2/1/2012 |
| Scott Pauls | Dartmouth College | 2/26/2012 - 3/2/2012 |
| Erik Kjær Pedersen | University of Copenhagen | 1/29/2012 - 2/1/2012 |
| John Pinney | Imperial College London | 2/25/2012 - 3/1/2012 |
| Carles Pons | University of Minnesota | 2/27/2012 - 3/2/2012 |
| Ely Porat | Bar-Ilan University | 2/12/2012 - 2/18/2012 |
| Candice Renee Price | University of Iowa | 8/1/2011 - 7/31/2012 |
| Natasha Przulj | Imperial College London | 2/26/2012 - 3/3/2012 |
| Natasha Przulj | Imperial College London | 2/12/2012 - 2/17/2012 |
| Teresa M Przytycka | National Center for Biotechnology Information | 2/26/2012 - 3/2/2012 |
| Karthik Pulivendal | University of Minnesota | 1/30/2012 - 2/1/2012 |
| Weifeng (Frederick) Qiu | University of Minnesota | 8/31/2010 - 8/30/2012 |
| Changzheng Qu | University of Minnesota | 1/30/2012 - 2/1/2012 |
| Anca Ruxandra Radulescu | University of Colorado | 1/29/2012 - 2/1/2012 |
| Ketan Rajawat | University of Minnesota | 2/27/2012 - 3/2/2012 |
| Parimala Raman | Emory University | 1/29/2012 - 2/1/2012 |
| Andrew Ranicki | University of Edinburgh | 1/29/2012 - 2/1/2012 |
| Ben J. Raphael | Brown University | 2/26/2012 - 3/3/2012 |
| Holger Rauhut | Rheinische Friedrich-Wilhelms-Universität Bonn | 2/25/2012 - 3/17/2012 |
| Douglas Conner Ravenel | University of Rochester | 1/29/2012 - 2/1/2012 |
| Victor Reiner | University of Minnesota | 1/30/2012 - 2/1/2012 |
| Sylvie Ricard-Blum | Université Claude-Bernard (Lyon I) | 2/12/2012 - 2/17/2012 |
| Luis Rocha | Indiana University | 2/26/2012 - 3/2/2012 |
| Jonathan Rogness | University of Minnesota | 1/30/2012 - 2/1/2012 |
| Dale Preston Odin Rolfsen | University of British Columbia | 1/29/2012 - 2/1/2012 |
| Xavier Ronaled | University of Minnesota | 1/30/2012 - 2/1/2012 |
| Frederick Roth | University of Toronto | 2/26/2012 - 3/1/2012 |
| Lee Rudolph | Clark University | 1/29/2012 - 2/1/2012 |
| Atri Rudra | University at Buffalo (SUNY) | 2/12/2012 - 2/17/2012 |
| Derek Ruths | McGill University | 2/26/2012 - 3/2/2012 |
| Vyacheslav V. Rykov | University of Nebraska | 2/12/2012 - 2/19/2012 |
| S. Cenk Sahinalp | Simon Fraser University | 2/26/2012 - 3/3/2012 |
| Venkatesh Saligrama | Boston University | 2/12/2012 - 2/17/2012 |
| Alex Samorodnitsky | Hebrew University | 2/11/2012 - 2/17/2012 |
| Sriram Sankararaman | Harvard Medical School | 2/12/2012 - 2/17/2012 |
| Guillermo R. Sapiro | University of Minnesota | 9/1/2011 - 5/31/2012 |
| Radmila Sazdanović | University of Pennsylvania | 1/29/2012 - 2/1/2012 |
| Robert Glenn Scharein | Hypnagogic Software | 1/5/2012 - 2/4/2012 |
| Alexander Schliep | Rutgers University | 2/12/2012 - 2/17/2012 |
| Michelle Kristin Schwalbe | National Research Council | 2/26/2012 - 3/2/2012 |
| George R Sell | University of Minnesota | 1/30/2012 - 2/1/2012 |
| Roded Sharan | Tel Aviv University | 2/26/2012 - 3/1/2012 |
| Noam Shental | Open University of Israel | 2/12/2012 - 2/16/2012 |
| Laurence Carl Siebenmann | Université de Paris XI (Paris-Sud) | 1/29/2012 - 2/3/2012 |
| Mona Singh | Princeton University | 2/26/2012 - 2/29/2012 |
| Steven Sperber | University of Minnesota | 1/30/2012 - 2/1/2012 |
| Karsten Steinhaeuser | University of Minnesota | 2/27/2012 - 3/2/2012 |
| Nathalie Stroeymeyt | Université de Lausanne | 2/25/2012 - 3/3/2012 |
| Karthik Subbian | University of Minnesota | 2/27/2012 - 3/2/2012 |
| Chiung-Jue Sung | National Tsing Hua University | 1/30/2012 - 2/1/2012 |
| Arthur Szlam | University of Minnesota | 8/31/2011 - 8/30/2012 |
| Vladimir Temlyakov | University of South Carolina | 2/1/2012 - 5/31/2012 |
| Nicolas Thierry-Mieg | Centre National de la Recherche Scientifique (CNRS) | 2/12/2012 - 2/17/2012 |
| Ulrike Tillmann | University of Oxford | 1/28/2012 - 2/1/2012 |
| Vladimir D Tonchev | Michigan Technological University | 2/13/2012 - 2/18/2012 |
| Donald Towsley | University of Massachusetts | 2/27/2012 - 3/2/2012 |
| Masashi Toyoda | University of Tokyo | 2/26/2012 - 3/2/2012 |
| Victor Turchin | Kansas State University | 1/29/2012 - 2/1/2012 |
| Eric van den Berg | Telcordia | 2/26/2012 - 3/2/2012 |
| Benjamin VanderSluis | University of Minnesota | 2/27/2012 - 3/2/2012 |
| Fabio Vandin | Brown University | 2/26/2012 - 3/2/2012 |
| Divyanshu Vats | University of Minnesota | 8/31/2011 - 8/30/2012 |
| Jonathan Wahl | University of North Carolina | 1/30/2012 - 2/1/2012 |
| Adwait Walimbe | University of Minnesota | 1/30/2012 - 2/1/2012 |
| Lan Wang | University of Minnesota | 1/24/2012 - 5/12/2012 |
| Walter Willinger | AT&T Laboratories - Research | 2/26/2012 - 3/2/2012 |
| David P. Woodruff | IBM Research Division | 2/15/2012 - 2/17/2012 |
| Mary Wootters | University of Michigan | 2/12/2012 - 2/17/2012 |
| Zheyang Wu | Worcester Polytechnic Institute | 2/12/2012 - 2/17/2012 |
| Lingzhou Xue | University of Minnesota | 9/1/2011 - 6/30/2012 |
| Teng Zhang | University of Minnesota | 8/31/2011 - 8/30/2012 |
| Ke Zhu | University of Minnesota | 1/30/2012 - 2/1/2012 |
| Or Zuk | Broad Institute | 2/12/2012 - 2/17/2012 |
Legend:
Postdoc or Industrial Postdoc
Long-term Visitor
IMA Affiliates:
Arizona State University, Boeing, Colorado State University, Corning Incorporated, ExxonMobil, Ford, General Motors, Georgia Institute of Technology, Honeywell, IBM, Indiana University, Iowa State University, Korea Advanced Institute of Science and Technology (KAIST), Lawrence Livermore National Laboratory, Lockheed Martin, Los Alamos National Laboratory, Medtronic, Michigan State University, Michigan Technological University, Mississippi State University, Northern Illinois University, Ohio State University, Pennsylvania State University, Portland State University, Purdue University, Rice University, Sandia National Laboratories, Schlumberger Cambridge Research, Schlumberger-Doll, Seoul National University, Siemens, Telcordia, Texas A & M University, University of Central Florida, University of Chicago, University of Delaware, University of Houston, University of Illinois at Urbana-Champaign, University of Iowa, University of Kentucky, University of Maryland, University of Michigan, University of Minnesota, University of North Carolina, University of Notre Dame, University of Pennsylvania, University of Pittsburgh, University of Tennessee, University of Wisconsin-Madison, University of Wyoming, US Air Force Research Laboratory, Wayne State University, Worcester Polytechnic Institute, Zhejiang University