Cancer genome landscapes

BY IN Cancer genomics, Journal Club, Review NO COMMENTS YET , , , , ,

Over the past decade, comprehensive sequencing efforts have revealed the genomic landscapes of common forms of human cancer. In this review, Vogelstein at el. summarize what has been learned about cancer genomes from these sequencing studies and what this information has taught us about cancer biology and future cancer management strategies. Some key points of


Finding the indices of differences between two strings

BY IN Code, Python, Tutorials NO COMMENTS YET

Python command for finding indices of differences between two strings. command: >>> [i for i in xrange(len(x)) if x[i] != y[i]] example: >>> x = ‘LEIYNQPNQEGPFDVQETEIAVQAKQPDVEEILSKGQHLYKEKPATQPVK’ >>> y = ‘LEIYNQPNQEGPFDVKETEIAVQAKQPDVEEILSKGQHLYKEKPATQPVK’ >>> [i for i in xrange(len(x)) if x[i] != y[i]] [15] This is particularly useful for finding position difference between two DNA or protein alignments


The Use of Orthologous Sequences to Predict the Impact of Amino Acid Substitutions on Protein Function

BY IN Comparative genomics, Functional impact prediction, Journal Club NO COMMENTS YET , ,

For nonsynonymous coding variants, functional impact prediction algorithms frequently make use of conservation of amino acid substitutions observed among homologous proteins at a given site under the assumption substitutions occurring at well-conserved sites will deleteriously impact protein function and substitutions occurring at less conserved sites will be tolerated. In this study, Marini et al. examine


In silico analysis of missense substitutions using sequence-alignment based methods

BY IN Functional impact prediction, Journal Club, Review NO COMMENTS YET , , , , , , , ,

Computational classifiers classify missense substitutions as pathogenetic or neutral based on inferences from evolutionary conservation using protein multiple sequence alignments (PMSAs) of the gene of interest (and other features). In this review, Tavtigian et al. make suggestions with respect to the important aspects of creating PMSAs that are informative for classification (and more). In using


Congruency in the prediction of pathogenic missense mutations: state-of-the-art web-based tools

BY IN Functional impact prediction, Journal Club, Review NO COMMENTS YET , , , , , , ,

Deep sequencing initiatives are identified a remarkable quantity of single nucleotide polymorphisms yet only approximately half are nonsynonymous amino acid substitutions that could potentially affect protein function. A confusing array of tools are available to help identify the few gene-coding variants that actually cause or confer susceptibility to disease. In this brief, Castellana and Mazza


Sequence variation in G-protein-coupled receptors: analysis of single nucleotide polymorphisms

BY IN Functional impact prediction, Journal Club, Machine learning NO COMMENTS YET , , , , , , , ,

G-protein-coupled receptors (GPCRs) play an important role in many physiological processes such as signal transduction and are frequently the targets for the majority of prescription drugs such as beta-blockers and anti-histamines. Understanding the role of sequence variations such as SNPs in GPCRs has potential implications for elucidating disease pathogenesis mechanisms and drug efficacy issues. In


Prediction of Missense Mutation Functionality Depends on Both the Algorithm and Sequence Alignment Employed

BY IN Functional impact prediction, Journal Club 1 COMMENT , , , , , , , , ,

A number of algorithms have been developed to predict the impact of missense mutations on protein structure and function using sequence and structure-based approaches, notably SIFT, PolyPhen-2, Xvar, and Align-GVGD. In this study, Hicks et al. demonstrate that accurately predicting the impact of missense mutations on protein function depends on the algorithm used, the type