Links tagged with 'tumor cell line'

Found 11 links

Displaying 11 links

CancerResourceDatabase Content

http://bioinformatics.charite.de/cancerresource/

CancerResource, a database that integrates cancer-relevant relationships of compounds and targets from (i) literature mining and (ii) external resources complemented with (iii) essential experimental and supporting information on genes and cellular effects. CancerResource addresses the spectrum of research on compound-target interactions in natural sciences as well as in individualized medicine.

This content is being maintained by robertpreissner.

CENTDISTTool Content

http://compbio.ddns.comp.nus.edu.sg/~chipseq/centdist/

CENTDIST is a co-motif scanning program to identify co-transcription factors. CENTDIST ranks co-transcription factors based on their distribution around CHIP-seq peaks.

CLICTool Content

http://gexp2.kaist.ac.kr/clic

CLIC performs clustering analysis of large microarray datasets. Genes are first clustered in individual dimensions and then using the ordinal labels of clusters for each dimension, full dimension wide clustering is performed.

COSMICDatabase Content

http://www.sanger.ac.uk/genetics/CGP/cosmic/

COSMIC curates comprehensive information on somatic mutations in human cancer. Release v48 (July 2010) describes over 136,000 coding mutations in almost 542,000 tumour samples; of the 18,490 genes documented, 4803 (26%) have one or more mutations. Full scientific literature curations are available on 83 major cancer genes and 49 fusion gene pairs. Biomart allows more automated data mining and integration with other biological databases. Annotation of genomic features has become a significant focus. COSMIC integrates many diverse types of mutation information and is making much closer links with Ensembl and other data resources.

DynamicProteomics DBDatabase Content

http://www.weizmann.ac.il/mcb/UriAlon/DynamProt/

Dynamic Proteomics database contains information on the position and amounts of endogenous proteins in individual living human cells. This is based on the Library of Annotated Reporter Cell-clones (LARC). The Dynamic Proteomics interface facilitates searches for genes of interest, downloads of protein fluorescent movies and alignments of dynamics following drug addition.

ENCODE DCCDatabase Content

http://encodeproject.org/ENCODE/

The ENCODE project has a goal of cataloguing all the functional elements in the human genome. The ENCODE Data Coordination Center (DCC) serves as the central repository for ENCODE data. The DCC contains a collection of high-throughput, genome-wide data generated with technologies such as ChIP-Seq, RNA-Seq, DNA digestion and others. It includes sequences with quality scores, alignments, signals calculated from the alignments, and in most cases, element or peak calls calculated from the signal data. Each data set is available for visualization and download via the UCSC Genome Browser. ENCODE data can also be retrieved using a metadata system that captures the experimental parameters of each assay.

FANTOMDatabase Content

http://fantom.gsc.riken.jp/4/

The Functional Annotation Of the Mammalian Genome (FANTOM) is a database for the transcriptional network that regulates macrophage differentiation. Data comes from cap analysis of gene expression (CAGE), sequencing mRNA 5'-ends with a second-generation sequencer to quantify promoter activities even in the absence of gene annotation. Additional genome-wide experiments complement the setup including short RNA sequencing, microarray gene expression profiling on large-scale perturbation experiments and ChIP-chip for epigenetic marks and transcription factors.

IGRhCellIDDatabase Content

http://igrcid.ibms.sinica.edu.tw

IGRhCellID is designed to integrate eight cell identification methods including seven methods (STR profile, gender, immunotypes, karyotype, isoenzyme profile, TP53 mutation and mutations of cancer genes) available in various public databases and our method of profiling genome alterations of human cell lines. Users can search for human cell lines with deleted gene to serve as indigenous knock-out cell model, with amplified gene to be the cell models for testing therapeutic efficacy and with overlapped aberrant chromosomal loci for revealing common cancer genes.

miRGenDatabase Content

http://www.diana.pcbi.upenn.edu/miRGen

miRGen 2.0 is a database that aims to provide comprehensive information about the position of human and mouse microRNA coding transcripts and their regulation by transcription factors, including a unique compilation of both predicted and experimentally supported data. Expression profiles of microRNAs in several tissues and cell lines, single nucleotide polymorphism locations, microRNA target prediction on protein coding genes and mapping of miRNA targets of co-regulated miRNAs on biological pathways are also integrated into the database and user interface.