Titlebook: Research in Computational Molecular Biology; 26th Annual Internat Itsik Pe‘er Conference proceedings 2022 The Editor(s) (if applicable) and

CRAB

Parley

Multi-modal Genotype and?Phenotype Mutual Learning to?Enhance Single-Modal Input Based Longitudinal en feasible, and multimodal data analysis has attracted significant attention in bioinformatics. Although existing multimodal learning methods have shown superior ability in combining data from multiple sources, they are not directly applicable for many real-world biological and biomedical studies t

偉大

Fast, Flexible, and?Exact Minimum Flow Decompositions via?ILPence, and variants of it are powerful models in multiassembly problems in Bioinformatics (e.g.?RNA assembly). However, because this problem and its variants are NP-hard, practical multiassembly tools either use heuristics or solve simpler, polynomial-time solvable versions of the problem, which may

crutch

Co-linear Chaining with?Overlaps and?Gap Costsbly) to a reference. It is used as an intermediate step in several alignment tools that employ a seed-chain-extend strategy. Despite this popularity, efficient subquadratic-time algorithms for the general case where chains support anchor overlaps and gap costs are not currently known. We present alg

Conscientious

The Complexity of?Approximate Pattern Matching on?de Bruijn Graphsh with |.| edges that exactly matches a pattern of length ., a lower bound based on the Strong Exponential Time Hypothesis (SETH) implies an algorithm significantly faster than . time is unlikely [Equi ., ICALP 2019]. However, for many special graphs, such as de Bruijn graphs, the problem can be sol

點(diǎn)燃

ProTranslator: Zero-Shot Protein Function Prediction Using Textual Descriptionraging progress of existing computational approaches in protein function prediction, it remains challenging to annotate proteins to a novel function that is not collected in the Gene Ontology and does not have any annotated proteins. This limitation, a “side effect” from the widely-used multi-label

飾帶

甜瓜

FUME

DeepMinimizer: A Differentiable Framework for?Optimizing Sequence-Specific Minimizer Schemese: (a) a reformulation of the combinatorial solution space using a deep neural network re-parameterization; and (b) a fully differentiable approximation of the discrete objective. We demonstrate that our framework, ., discovers minimizer schemes that significantly outperform state-of-the-art constructions on genomic sequences.

FLAGR

0302-9743 n Diego, CA, USA in May 2022. The 17 regular and 23 short papers presented were carefully reviewed and selected from 188 submissions. The papers report on original research in all areas of computational molecular biology and bioinformatics..978-3-031-04748-0978-3-031-04749-7Series ISSN 0302-9743 Ser