RECOMB 2016 List of Accepted Papers Available

RECOMB 2016 Accepted Papers

RECOMB 2016 Accepted Papers

RECOMB 2016, 20th Annual International Conference on Research in Computational Molecular Biology, has recently announced the list of accepted papers. This year, RECOMB will be held in Santa Monica, California April 17-21, 2016.

RECOMB 2016 has accepted 35 papers from a variety of computational biology topics. The accepted papers will be presented as talks at RECOMB. RECOMB 2016’s accepted papers have the option to be considered for Journal of Computational Biology. This year, RECOMB is partnering with the Journal Cell Systems and selected accepted papers will be considered for expedited review at Cell Systems.

RECOMB 2016 keynote speakers include Rob Knight, University of California, San Diego, and Leonid Kruglyak, University of California, Los Angeles. In addition to the main RECOMB conference and the RECOMB Satellite meetings (RECOMB-seq, RECOMB-Genetics, and RECOMB-CCB), this year’s RECOMB also has a special Mike Waterman Symposium in honor of Michael Waterman’s 75th birthday and his contributions to RECOMB.

Here is a list of few accepted papers.

  • Hao Wang, Joel McManus and Carl Kingsford. Accurate Recovery of Ribosome Positions Reveals Slow Translation of Wobble-Pairing Codons in Yeast
  • David Pellow, Darya Filippova and Carl Kingsford. Improving Bloom filter performance on sequence data using k-mer Bloom filters
  • Yael Steuerman and Irit Gat-Viks. Exploiting Gene-Expression Deconvolution to Probe the Genetics of the Immune System
  • Kristoffer Sahlin, Mattias Frånberg and Lars Arvestad. Structural variation detection with read pair information — An improved null-hypothesis reduces bias
  • Alexandru I. Tomescu and Paul Medvedev. Safe and complete contig assembly via omnitigs
  • Ahmed Sobih, Alexandru I. Tomescu and Veli Mäkinen. MetaFlow: Metagenomic profiling based on whole-genome coverage analysis with min-cost flows
  • Sergey Nurk, Dmitry Meleshko and Pavel Pevzner. metaSPAdes: a new versatile de novo metagenomics assembler
  • Sean Simmons, Cenk Sahinalp and Bonnie Berger. Enabling Privacy-Preserving GWAS in Heterogenous Human Populations
  • Chandler Zuo, Kailei Chen and Sunduz Keles. A MAD-Bayes Algorithm for State-space Inference and Clustering with Application to Querying Large Collections of ChIP-Seq Data Sets
  • Alexander Artyomenko, Nicholas Wu, Serghei Mangul, Eleazar Eskin, Ren Sun and Alex Zelikovsky. Long single-molecule reads can resolve the complexity of the Influenza virus composed of rare, closely related mutant variants
  • Joshua Welch, Ziqing Liu, Li Wang, Junjie Liu, Paul Lerou, Jeremy Purvis, Li Qian, Alexander Hartemink and Jan Prins. SLICER: Inferring Branched, Nonlinear Cellular Trajectories from Single Cell RNA-seq Data
  • Mingfu Shao and Bernard Moret. On Computing Pairwise Breakpoint Distances
  • Emre Sefer and Ziv Bar-Joseph. Shall we dense? Comparing design strategies for time series expression experiments
  • Nilgun Donmez, Salem Malikic, Alexander Wyatt, Colin Collins, Martin Gleave and Cenk Sahinalp. Clonality inference from single tumor samples using low coverage sequence data
  • Chenchen Zou, Yuping Zhang and Zhengqing Ouyang. Multi-track modeling for genome-scale reconstruction of 3D chromatin structure from Hi-C data
  • John Wiedenhoeft, Eric Brugel and Alexander Schliep. Fast Bayesian Inference of Copy Number Variants using Hidden Markov Models with Wavelet Compression
  • Yu Lin, Max W. Shen, Jeffrey Yuan and Pavel Pevzner. Assembly of Long Error-Prone Reads Using de Bruijn Graphs
  • Mohammed El-Kebir, Gryte Satas, Layla Oesper and Ben Raphael. Multi-State Perfect Phylogeny Mixture Deconvolution and Applications to Cancer Sequencing
  • Yang Li, Shiguo Zhou, David Schwartz and Jian Ma. Allele-Specific Quantification of Structural Variations in Cancer Genomes
  • Yunan Luo, Jianyang Zeng, Bonnie Berger and Jian Peng. Low-density locality-sensitive hashing boosts metagenomic binning
  • Katharina Jahn, Jack Kuipers and Niko Beerenwinkel. Tree inference for single-cell data
  • Victoria Popic and Serafim Batzoglou. Efficient Privacy-Preserving Read Mapping Using Locality Sensitive Hashing and Secure Kmer Voting


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