Introduction to Computational Molecular Biology

TL;DR: This chapter focuses on methods that can quickly and precisely establish whether two reads are similar or not and that allow to analyze biological sequences extracted with NGS technologies.

TL;DR: In this article, the ligand-induced conformational adaptations result from both hydrophobic and electrostatic forces, and they could be used for further virtual screening studies to identify potential lead-like molecules.

TL;DR: Plasmid vectors puc57, pKLAC1-malE, pTXB1 and phage vector Adenovirus2 were used to prove that computational time for solving genome map assembly problem using constraint automaton solution is linear with both precise and approximate data.

TL;DR: The second edition of a quarterly column as discussed by the authors provides a continuing update to the list of problems (NP-complete and harder) presented by M. R. Garey and myself in our book "Computers and Intractability: A Guide to the Theory of NP-Completeness,” W. H. Freeman & Co., San Francisco, 1979.

TL;DR: The updated new edition of the classic Introduction to Algorithms is intended primarily for use in undergraduate or graduate courses in algorithms or data structures and presents a rich variety of algorithms and covers them in considerable depth while making their design and analysis accessible to all levels of readers.

TL;DR: Recent developments of statistical methods in molecular phylogenetics are reviewed and it is shown that the mathematical foundations of these methods are not well established, but computer simulations and empirical data indicate that currently used methods produce reasonably good phylogenetic trees when a sufficiently large number of nucleotides or amino acids are used.