Research in Computational Molecular Biology: 21st Annual International Conference, RECOMB 2017, Hon

Boosting alignment accuracy by adaptive local realignment.- A concurrent subtractive assembly approach for identification of disease associated sub-meta-genomes.- A flow procedure for the linearization of genome variation graphs.- Dynamic alignment-free and reference-free read compression.- A fast approximate algorithm for mapping long reads to large reference databases.- Determining the consistency of resolved triplets and fan triplets.- Progressive calibration and averaging for tandem mass spectrometry statistical confidence estimation: Why settle for a single decoy.- Resolving multi-copy duplications de novo using polyploid phasing.- A Bayesian active learning experimental design for inferring signaling networks.- BBK* (Branch and Bound over K*): A provable and efficient ensemble-based algorithm to optimize stability and binding affinity over large sequence spaces.- Super-bubbles, ultra-bubbles and cacti.- EPR-dictionaries: A practical and fast data structure for constant time searches in unidirectional and bidirectional FM indices.- A Bayesian framework for estimating cell type composition from DNA methylation without the need for methylation reference.- Towards recovering Allele-specific cancer genome graphs.- Using stochastic approximation techniques to efficiently construct confidence intervals for heritability.- Improved search of large transcriptomic sequencing databases using split sequence bloom trees.- All some sequence bloom trees.- Longitudinal genotype-phenotype association study via temporal structure auto-learning predictive model.- Improving imputation accuracy by inferring causal variants in genetic studies.- The copy-number tree mixture deconvolution problem and applications to multi-sample bulk sequencing tumor data.- Quantifying the impact of non-coding variants on transcription factor-DNA binding.- aBayesQR: A Bayesian method for reconstruction of viral populations characterized by low diversity.- BeWith: A between-within method for module discovery in cancer using integrated analysis of mutual exclusivity, co-occurrence and functional interactions.- K-mer Set Memory (KSM) motif representation enables accurate prediction of the impact of regulatory variants.- Network-based coverage of mutational profiles reveals cancer genes.- Ultra-accurate complex disorder prediction: case study of neurodevelopmental disorders.- Inference of the human polyadenylation Code.- Folding membrane proteins by deep transfer learning.- A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information.- Epistasis in genomic and survival data of cancer patients.- Ultra-fast identity by descent detection in biobank-scale cohorts using positional burrows-wheeler transform.- Joker de Bruijn: sequence libraries to cover all k-mers using joker characters.- GATTACA: Lightweight metagenomic binning using kmer counting.- Species tree estimation using ASTRAL: how many genes are enough.- Reconstructing antibody repertoires from error-prone immune-sequencing datasets.- NetREX: Network rewiring using EXpression - Towards context specific regulatory networks.- E pluribus unum: United States of single cells.- ROSE: a deep learning based framework for predicting ribosome stalling.