Titlebook: Research in Computational Molecular Biology; 24th Annual Internat Russell Schwartz Conference proceedings 2020 Springer Nature Switzerland

愤慨点吧

适宜

Bagging MSA Learning: Enhancing Low-Quality PSSM with Deep Learning for Accurate Protein Structure Pk. Structure property prediction models are then built upon such enhanced PSSM features for more accurate predictions. Empirical evaluation of CB513, CASP11, and CASP12 datasets indicate that our unsupervised enhancing scheme indeed generates more informative PSSM features for structure property prediction.

斜谷

西瓜

: Fast and Optimal Sequence-to-Graph Alignmenting subsequence in the query to be aligned, resulting in a provably optimal alignment algorithm called ...Experimental evaluation of . shows that it is 1–2 orders of magnitude faster than state-of-the-art optimal algorithms on the task of aligning Illumina reads to reference genome graphs. Implementations and evaluations are available at ..

Headstrong

Computing the Rearrangement Distance of Natural Genomesclude the polynomial-time computability of the inversion distance by Hannenhalli and Pevzner in 1995 and the introduction of the double-cut and join (DCJ) distance by Yancopoulos, Attie and Friedberg in 2005. Both results, however, rely on the assumption that the genomes under comparison contain the

exhilaration

Deep Large-Scale Multi-task Learning Network for Gene Expression Inferenceerimental conditions. Despite the recent advances in high-throughput technologies, profiling the whole-genome set is still challenging and expensive. Based on the fact that there is high correlation among the expression patterns of different genes, the above issue can be addressed by a cost-effectiv

打折

A Randomized Parallel Algorithm for Efficiently Finding Near-Optimal Universal Hitting Setsy introduced as an alternative to the central idea of minimizers in sequence analysis with the hopes that they could more efficiently address common tasks such as computing hash functions for read overlap, sparse suffix arrays, and Bloom filters. A UHS is a set of .-mers that hit every sequence of l

没有希望

Multiple Competition-Based FDR Control and Its Application to Peptide Detections gained significant popularity in other fields after Barber and Candés laid its theoretical foundation in a more general setting that included the feature selection problem [.]. In both cases, the competition is based on a head-to-head comparison between an observed score and a corresponding decoy/

Jingoism

Supervised Adversarial Alignment of Single-Cell RNA-seq Data of the profiled cells, such representations are used by many downstream analyses methods ranging from pseudo-time reconstruction to clustering to alignment of scRNA-seq data from different experiments, platforms, and labs. Both supervised and unsupervised methods have been proposed to reduce the di

Misnomer

Bagging MSA Learning: Enhancing Low-Quality PSSM with Deep Learning for Accurate Protein Structure Pnction of a protein. PSSM (Position-Specific Scoring Matrix) features are widely used in the structure property prediction. However, some proteins may have low-quality PSSM features due to insufficient homologous sequences, leading to limited prediction accuracy. To address this limitation, we propo