Introduction to Computational Molecular Biology

TL;DR: This work consists of a study of some sequence comparison tools, aiming using them as a mapping tool of contigs of an incomplete genome onto a close related complete genome to help projects in which the goal is just understanding important biological features without finishing the whole genome.

TL;DR: The major results contained in this thesis provide a linear time transformation from an arbitrary permutation into its equivalent simple permutation, and an O(n log …) time transformation to solve genome rearrangement problems.

TL;DR: Initial results indicate that it is possible to obtain substitution matrices whose performance is either comparable to or surpasses that of several others and given computational results on the BAliBASE suite using a genetic algorithm for optimization.

TL;DR: In this article, the authors present methods for determining if a subject is at risk for developing neurotoxicity following administration of a therapy, such as an immunotherapy or cell therapy, e.g., a chimeric antigen receptor (CAR) T cell therapy based on the expression, in a sample obtained from the subject, of one or more genes or gene products that are associated with and/or correlate to a risk of developing toxicity following the therapy.

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.