Saturday April 21st

Sunday April 22rd

Monday April 23rd

Tuesday April 24th

The scientific program also includes 150 selected posters, whose titles/authors can be found on a separate page.

Session 1 – Cancer

  • Dana Silverbush, Simona Cristea, Gali Yanovich, Tamar Geiger, Niko Beerenwinkel and Roded SharanModulOmics: Integrating Multi-Omics Data to Identify Cancer Driver Modules
  • Rebecca Sarto Basso, Dorit Hochbaum and Fabio VandinEfficient Algorithms to Discover Alterations with Complementary Functional Association in Cancer

Session 2 – Sequencing

  • Ariya Shajii, Ibrahim Numanagić and Bonnie BergerLatent variable model for aligning barcoded short-reads improves downstream analyses
  • Mehrdad Bakhtiari, Sharona Shleizer-Burko, Melissa Gymrek, Vikas Bansal and Vineet BafnaTargeted Genotyping of Variable Number Tandem Repeats with adVNTR
  • Mikhail Kolmogorov, Jeffrey Yuan, Yu Lin and Pavel PevznerAssembly of Long Error-Prone Reads and Repeat Classification
  • Prashant Pandey, Fatemeh Almodaresi, Michael A. Bender, Michael Ferdman, Rob Johnson and Rob PatroMantis: A Fast, Small, and Exact Large-Scale Sequence-Search Index

Session 3 – Proteomics

  • Sujun Li, Alex Decourcy and Haixu TangConstrained De Novo Sequencing of neo-Epitope Peptides using Tandem Mass Spectrometry
  • Alexey Gurevich, Alla Mikheenko, Alexander Shlemov, Anton Korobeynikov, Hosein Mohimani and Pavel Pevzner[Highlight] Increased diversity of peptidic natural products revealed by modification-tolerant database search of mass spectra

Session 4 – Deep Learning

  • Yunan Luo, Jianzhu Ma, Yang Liu, Qing Ye, Trey Ideker and Jian PengDeciphering signaling specificity with deep neural networks
  • Tristan Bepler, Andrew Morin, Alex Noble, Julia Brasch, Lawrence Shapiro and Bonnie BergerPositive-unlabeled convolutional neural networks for particle picking in cryo-electron micrographs
  • Tianming Zhou, Sheng Wang and Jinbo XuDeep learning reveals many more inter-protein residue-residue contacts than direct coupling analysis
  • Hieu Tran, Xianglilan Zhang, Lei Xin, Baozhen Shan and Ming Li[Highlight] De novo Peptide Sequencing by Deep Learning

Session 5 – Cross-Species Functional Genomics

  • Mark Leiserson, Jason Fan, Anthony Cannistra, Inbar Fried, Tim Lim, Thomas Schaffner, Mark Crovella and Benjamin HescottA Multi-Species Functional Embedding Integrating Sequence and Network Structure
  • Yang Yang, Quanquan Gu, Takayo Sasaki, Rachel O’neill, David Gilbert and Jian MaContinuous-trait probabilistic model for comparing multi-species functional genomic data

Session 6 – Algorithmic Foundations

  • Sharma V. Thankachan, Chaitanya Aluru, Sriram P. Chockalingam and Srinivas AluruAlgorithmic Framework for Approximate Matching Under Bounded Edits with Applications to Sequence Analysis
  • Anna Kuosmanen, Topi Paavilainen, Travis Gagie, Rayan Chikhi, Alexandru I. Tomescu and Veli MäkinenUsing Minimum Path Cover to Boost Dynamic Programming on DAGs: Co-Linear Chaining Extended
  • Ali Ebrahimpour Boroojeny, Akash Shrestha, Ali Sharifi-Zarchi, Suzanne Gallagher, S. Cenk Sahinalp and Hamidreza ChitsazGTED: Graph Traversal Edit Distance
  • Yaron OrensteinReverse de Bruijn: Utilizing Reverse Peptide Synthesis to Cover All Amino Acid k-mers

Session 7 – Genome Organization

  • Linh Huynh and Fereydoun HormozdiariContribution of structural variation to genome structure: TAD fusion discovery and ranking
  • Alon Diament and Tamir Tuller[Highlight] Tracking the evolution of 3D gene organization demonstrates its connection to phenotypic divergence

Session 8 – Cancer Phylogenetics

  • Jochen Singer, Jack Kuipers, Katharina Jahn and Niko BeerenwinkelSCIPhI: Single-cell mutation identification via phylogenetic inference
  • Salem Malikic, Katharina Jahn, Jack Kuipers, S. Cenk Sahinalp and Niko BeerenwinkelIntegrative inference of subclonal tumor evolution from single-cell and bulk sequencing data

Session 9 – Evolution

  • Sebastien Roch and Kun-Chieh WangCircular Networks from Distorted Metrics
  • Gary Larson, Scott Schmidler and Jeffrey ThorneModeling Dependence in Evolutionary Inference for Proteins

Session 10 – Genetics And Association Studies

  • Tyler Joseph and Itsik Pe’ErInference of population structure from ancient DNA
  • Yue Wu, Sriram Sankararaman and Eleazar EskinA unifying framework for summary statistics imputation
  • Elior Rahmani, Regev Schweiger, Saharon Rosset, Sriram Sankararaman and Eran HalperinTensor Composition Analysis Detects Cell-Type Specific Associations in Epigenetic Studies
  • Tyler Cowman and Mehmet Koyuturk[Highlight] Prioritizing Tests of Epistasis Through Hierarchical Representation of Genomic Redundancies

Session 11 – Single-Cell Analysis

  • Hyunghoon Cho, Bonnie Berger and Jian PengGeneralizable visualization of mega-scale single-cell data
  • Ghislain Durif, Laurent Modolo, Jeff E. Mold, Sophie Lambert-Lacroix and Franck PicardProbabilistic Count Matrix Factorization for Single Cell Expression Data Analysis

Session 12 – Metagenomics And Microbiome

  • Anton Bankevich and Pavel PevznerLong Reads Enable Accurate Estimates Of Complexity Of Metagenomes
  • Zhemin Zhou, Nina Luhmann, Nabil-Fareed Alikhan, Christopher Quince and Mark AchtmanAccurate Reconstruction of Microbial Strains Using Representative Reference Genomes

Session 13 – Functional Genomics And Metagenomics

  • Shahab Sarmashghi, Kristine Bohmann, M. Thomas P. Gilbert, Vineet Bafna and Siavash MirarabAssembly-free and alignment-free barcoding from genome skims
  • Naomi Yamada, William K.M. Lai, Nina Farrell, B. Franklin Pugh and Shaun MahonyCharacterizing protein-DNA binding event subtypes in ChIP-exo data
  • Shounak Chakraborty, Stefan Canzar, Tobias Marschall and Marcel H. SchulzChromatyping: Reconstructing nucleosome profiles from NOMe sequencing data
  • Jingyi Jessica Li, Guo-Liang Chew and Mark DBiggin[Highlight] Quantitating translational control: mRNA abundance-dependent and independent contributions and the mRNA sequences that specify them

Session 14 – Learning And Inference

  • Yuriy Sverchkov, Yi-Hsuan Ho, Audrey Gasch and Mark CravenContext-Specific Nested Effects Models
  • Cyril Galitzine, Pierre Jean Beltran, Ileana Cristea and Olga VitekStatistical inference of peroxisome dynamics
  • Franziska Görtler, Stefan Solbrig, Tilo Wettig, Peter J. Oefner, Rainer Spang and Michael AltenbuchingerLoss-function learning for digital tissue deconvolution

Session 15 – RNA

  • Stefan Hammer, Yann Ponty, Wei Wang and Sebastian WillFixed-Parameter Tractable Sampling for RNA Design with Multiple Target Structures
  • Yijie Wang, Jan Hoinka, Piotr Swiderski and Teresa PrzytyckaAptaBlocks: Accelerating the Design of RNA-based Drug Delivery Systems
  • Antoine Soulé, Jean-Marc Steyaert and Jerome WaldispuhlA nested 2-level cross-validation ensemble learning pipeline suggests a negative pressure against crosstalk snoRNA-mRNA interactions in Saccharomyces Cerevisae
  • Edouard Bonnet, Paweł Rzążewski and Florian SikoraDesigning RNA Secondary Structures is Hard