In graph theory, a string graph is an intersection graph of curves in the plane; each curve is called a "string". String graphs were first proposed by E. W. Myers in a 2005 publication.
github.com - The RAVEN (Reconstruction, Analysis and Visualization of Metabolic Networks) Toolbox 2 is a software suite for Matlab that allows for semi-automated reconstruction of genome-scale models (GEMs). It makes use of published models and/or KEGG, MetaCyc...
hub.docker.com - GPSRdocker (http://webs.iiitd.edu.in/gpsrdocker/) is Presently it contain software developed at G. P. S. Raghava's group (http://webs.iiitd.edu.in/raghava/ ).
The programs and the package are free software for academic users. Permission...
github.com - OMTools, an efficient and intuitive data processing and visualization suite to handle and explore large-scale optical mapping profiles. OMTools includes modules for visualization (OMView), data processing and simulation. These modules together form...
http://www.ub.edu/dnasp/ - DnaSP, DNA Sequence Polymorphism, is a software package for the analysis of DNA polymorphisms using data from a single locus (a multiple sequence aligned -MSA data), or from several loci (a Multiple-MSA data, such as formats generated by some...
http://genometools.org/ - The GenomeTools genome analysis system is a free collection of bioinformatics tools (in the realm of genome informatics) combined into a single binary named gt. It is based on a C library named...
https://js.cgview.ca/ - CGView.js is a Circular Genome Viewing tool for visualizing and interacting with small genomes. This software is an adaptation of the Java program CGView.
CGView.js is the genome viewer of Proksee, an expert system for genome...
Laboratory of Statistics and Computational tools for Bioinformatics
The Laboratory of Statistics and Computational tools for Bioinformatics (BioinfoLab) is hosted at the Istituto per le Applicazioni del Calcolo "Mauro Picone" - CNR . The...
Huge amounts of genotype data are being produced with recent technological advances, both from increasingly comprehensive and inexpensive genome-wide SNP microarrays and from ever more accessible whole-genome and whole-exome sequencing methods