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The main focus of this Computational Biology group is to predict function and to gain insights into evolution by comparative analysis of complex molecular data. The group currently works on three different scales: * genes and proteins, * protein networks and cellular processes, and * phenotypes and environments. They require both tool development and applications. Some selected projects include comparative gene, genome and metagenome analysis, mapping interactions to proteins and pathways as well as the study of temporal and spatial protein network aspects. All are geared towards the bridging of genotype and phenotype through a better understanding of molecular and cellular processes. The services - resources & tools, developed by Bork Group, are mainly designed and maintained for research & academic purposes. Most of services are published and documented in one or more papers. All our tools can be completely customized and integrated into your existing framework. This service is provided by the company biobyte solutions GmbH. Please visit their tools and services pages for full details and more information. Standard commercial licenses for our tools are also available through biobyte solutions GmbH. The group is partially associated with Max Delbr��ck Center for Molecular Medicine (MDC), Berlin.
Proper citation: EMBL - Bork Group (RRID:SCR_000810) Copy
http://sv.gersteinlab.org/pemer/
Software package as computational framework with simulation-based error models for inferring genomic structural variants from massive paired-end sequencing data. Package is composed of three modules, PEMer workflow, SV-Simulation and BreakDB. PEMer workflow is a sensitive software for detecting SVs from paired-end sequence reads. SV-Simulation randomly introduces SVs into a given genome and generates simulated paired-end reads from novel genome.
Proper citation: PEMer (RRID:SCR_005263) Copy
THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. A database of candidate genes for mapped inherited human diseases. Candidate priorities are automatically established by a data mining algorithm that extracts putative genes in the chromosomal region where the disease is mapped, and evaluates their possible relation to the disease based on the phenotype of the disorder. Data analysis uses a scoring system developed for the possible functional relations of human genes to genetically inherited diseases that have been mapped onto chromosomal regions without assignment of a particular gene. Methodology can be divided in two parts: the association of genes to phenotypic features, and the identification of candidate genes on a chromosonal region by homology. This is an analysis of relations between phenotypic features and chemical objects, and from chemical objects to protein function terms, based on the whole MEDLINE and RefSeq databases.
Proper citation: Candidate Genes to Inherited Diseases (RRID:SCR_008190) Copy
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