Search Results for "community detection algorithm"

Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout (MAGeCK) is a computational tool to identify important genes from the recent genome-scale CRISPR-Cas9 knockout screens technology. For instructions and documentations, please refer to the wiki page. MAGeCK is developed by Wei Li and Han Xu from Dr. Xiaole Shirley Liu's lab at Dana-Farber Cancer Institute/Harvard School of Public Health, and is maintained by Wei Li lab at Children's National Medical Center. We thank the support...

During the past few years, whole exome sequencing has imposed itself for genetic research, largely due to its use for detection of causative mutations responsible for Mendelian disorders. As a consequence of their power and of the rapidly decreasing cost of these technologies, massive amount of exome sequencing data are generated and becoming available to a broadening community of scientists. However, these data remain difficult to analyze and interpret by the general scientific community, due to the limited bioinformatics resources that are currently freely available for their analysis and the partial information that they provide. ...

This software detects homologous recombination events (HREs) from SNP data. Based on SNP alleles calls and locations, it breaks the genomes into locally colinear blocks, and looks for cases where SNPs do not agree with the vertical pattern of inheritance in a phylogeny. It applies a dynamic programming algorithm to model whether changes within a block are likely a result of mutations, sequencing errors, or HRE. We use information from the nearby SNPs, so that if 1-2 alleles in a series of...

The RDXplorer is a computational tool for copy number variants (CNV) detection in whole human genome sequence data using read depth (RD) coverage. CNV detection is based on the Event-Wise Testing (EWT) algorithm recently published by our group.

This is a Python program based on the NegEx algorithm that detects the polarity of the clinical evidence in clinical random trials. If you use this code please cite this paper: P. Davis-Desmond and Diego Mollá. Detection of Evidence in Clinical Research Papers (2012). Australasian Workshop On Health Informatics and Knowledge Management (HIKM 2012), Melbourne, Australia. http://www.ics.mq.edu.au/~diego/publications/hikm12.pdf