Fold [class] recognized by an…[NN] predictor based-on evolutionary & structural info., w/ particle-swarm training
http://onlinelibrary.wiley.com/doi/10.1002/jcc.24232/full
Ngaam J. Cheung,
Xue-Ming Ding,
Hong-Bin Shen
First published: 27 October 2015
DOI: 10.1002/jcc.24232
Model-Based Approach to Inferring…#Cancer Mutation Signatures http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1005657 Assuming independence betw 3 NTs, 11 v 95 parameters
QT:{{”
The first contribution of this paper is to suggest a more parsimonious approach to modelling mutation signatures, with the benefit of producing both more stable estimates and more easily interpretable signatures. In brief, we substantially reduce the number of parameters per signature by breaking each mutation pattern into “features”, and assuming independence across mutation features. For example, consider the case where a mutation pattern is defined by the substitution and its two flanking bases. We break this into three features
(substitution, 3′ base, 5′ base), and characterize each mutation signature by a probability distribution for each feature (which, by our independence assumption, are multiplied together to define a distribution on mutation patterns). Since the number of possible values for each feature is 6, 4, and 4 respectively this requires 5 + 3 + 3 = 11 parameters instead of 96 − 1 = 95 parameters. Furthermore, extending this model to account for ±n neighboring bases requires only 5 + 6nparameters instead of 6 × 42n − 1. For example, considering ±2 positions requires 17 parameters instead of 1,535. Finally,
incorporating transcription strand as an additional feature adds just one parameter, instead of doubling the number of parameters. “}}
Neutral tumor #evolution across #cancer types
http://www.nature.com/ng/journal/v48/n3/full/ng.3489.html Initial burst of driver events followed by random mutations
#Thermodynamics of Antimicrobial Lipopeptide Binding to Membranes http://www.cell.com/biophysj/abstract/S0006-3495(14)00928-X Non-human selectivity studied w. coarse-grained MD
A Multiscale Coarse-Graining Method for Biomolecul[es] http://pubs.acs.org/doi/abs/10.1021/jp044629q Simplified force field from fitting to all-atom #simulations
Sergei Izvekov and Gregory A. Voth *
J. Phys. Chem. B, 2005, 109 (7), pp 2469–2473
DOI: 10.1021/jp044629q
Syntrophic exchange in synthetic #microbial communities [& their evolution] http://www.pnas.org/content/111/20/E2149.abstract Trading metabolically costly amino acids
WGBS…reveals complementary roles of promoter & gene-body
#methylation in…regulation http://genomebiology.com/content/15/7/408 Has model for gene expression
Mirsynergy: detecting synergistic #miRNA regulatory modules by… neighborhood expansion
http://www.ncbi.nlm.nih.gov/pubmed/24894504 creates overlapping clusters