Search Results for "gene"

A Tool for Retrieval, Visualization and Analysis of biological Pathways. Import a Gene or Protein Set from any Excel file. Automatically find signaling Pathways from KEGG. Integrate your Data in Seconds with a live interactive Force-directed Layout.

OASIS is an application that enables complex analytical queries across somatic mutations; copy number changes (CNV); and gene expression data. OASIS has been built on top of the BIoMart frameworks and has been extended to incorporate unique tools and visualizations to facilitate analysis of complex cancer "Omics" datasets.

...A host of annotations are provided: orthologous and paralogous multiple sequence alignments, UCSC annotations, reports detailing conservation of a nsSNP in alignments, and links to external nsSNP and gene information such as relevant publications. GESPA is connected to a constantly updating SQL server allowing for fast data retrieval. NOTE: REQUIRES Java 1.7.0+. Port 1433 cannot be blocked by firewall, network, or antivirus program. Please cite: http://tinyurl.com/oj7p84a

...This may be useful to reverse-engineer human constructs like electronic equipment, manufactured machines, or bureaucratic hierarchies; but also to decompose natural constructs like gene-relation or protein-relation nets.

Use statistical methods to analyze time-course data (gene expression microarray and RNA-seq data in particular, but not limited to). Apply significance tests to filter out only significant genes or time series. Cluster time series into similar groups. Generate network models, including linear or non-linear models. Variable selection and optimization routines included. Written in Scala and R.

The BioNLP UIMA Component Repository provides UIMA wrappers for novel and well-known 3rd-party NLP tools used in biomedical text prosessing, such as tokenizers, parsers, named entity taggers, and tools for evaluation.

SLEDRIDE: Simplified Learning about Expression Data Running in a Desktop Environment. To provide a general workbench for pipe-lining microarray gene expression data from supervised learning results into unsupervised learning methods.

Jeep is a modular, abstract and distributed evolutionnary programming core written in Java, allowing to grow autonomous agents as well a gene pool (as in genetic algorithms).