Titlebook: Research in Computational Molecular Biology; 18th Annual Internat Roded Sharan Conference proceedings 2014 Springer International Publishin

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MRFalign: Protein Homology Detection through Alignment of Markov Random Fields,nces. So far the most sensitive method for homology detection is based upon comparison of protein sequence profiles, which are usually derived from multiple sequence alignment (MSA) of sequence homologs in a protein family and represented as a position-specific scoring matrix (PSSM) or an HMM (Hidde

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An Integrated Model of Multiple-Condition ChIP-Seq Data Reveals Predeterminants of Cdx2 Binding,ulator can bind to distinct sets of genomic targets depending on the cellular context in which it is expressed. Characterizing the determinants of such differential binding specificity is key to understanding how a single regulator can play multiple roles during development and other dynamic cellula

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Building a Pangenome Reference for a Population,ted subspecies. Given a set of genomes partitioned by homology into alignment blocks we formalise the problem of ordering and orienting the blocks such that the resulting ordering maximally agrees with the underlying genomes’ ordering and orientation, creating a pangenome reference ordering. We show

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CSAX: Characterizing Systematic Anomalies in eXpression Data,ith similar molecular phenotypes. Here, we address the question of what can be done when it is relatively easy to obtain healthy patient samples, but when abnormalities corresponding to disease states may be rare and one-of-a-kind. The associated computational challenge, anomaly detection, is a well

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,: Haplotype Assembly for Future-Generation Sequencing Reads, beyond just detecting them. The resulting haplotypes, lists of SNPs belonging to each copy, are crucial for downstream analyses in population genetics. Currently, statistical approaches, which avoid making use of direct read information, constitute the state-of-the-art. ., which addresses phasing d

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Changepoint Analysis for Efficient Variant Calling,processed using more computationally expensive methods. . runs on a deeply sequenced human whole genome sample in approximately 20 minutes, potentially reducing the burden of variant calling by an order of magnitude after one memory-efficient pass over the data.