A number of reviews on immunology from the Riken Institute in Japan
Showing posts with label useful sites. Show all posts
Showing posts with label useful sites. Show all posts
Allen Brain Atlas - The human brain whole genome transcriptome
An "all genes, all structures" gene expression survey in multiple adult control brains.
- > 62,000 gene probes per profile
- ~ 500 samples per hemisphere across cerebrum, cerebellum and brainstem
- Data mapped with histology into unified 3-D anatomic framework based on MRI
PLOS Computational Biology: An Online Bioinformatics Curriculum
This reviews the many online bioinformatics courses available.
List of Free Statistical Software
A list of links to free statistics programs, including bioinformatics,
psychometrics, econometrics, simulations, database, data mining and
spreadsheets software; and some mathematical software (if it is useful
in statistics).
The list shouldn’t include demo/student versions (unless highly functional) or temporary trial versions. Scripts to be run within a program shouldn’t be included in this list.
The list shouldn’t include demo/student versions (unless highly functional) or temporary trial versions. Scripts to be run within a program shouldn’t be included in this list.
GENEVESTIGATOR - shaping biological discovery
Genevestigator is a high performance search engine for gene expression. Our focus is on the deep integration of high quality, well annotated data with high-performance computing. This allows users to run unique types of queries across thousands of datasets simultaneously.
GENEVESTIGATOR - shaping biological discovery
Genevestigator is a high performance search engine for gene expression. Our focus is on the deep integration of high quality, well annotated data with high-performance computing. This allows users to run unique types of queries across thousands of datasets simultaneously.
Dr.VIS Human Disease-Related Viral Integration Sites Database
Dr.VIS collects and locates human disease-related viral integration sites. So far, about 600 sites covering 5 virus organisms and 11 human diseases are available. Integration sites in Dr.VIS are located against chromesome, cytoband, gene and refseq position as specific as possible. Viral-cellular junction sequences are extracted from papers and nucleotide databases, and linked to cooresponding integration sites Graphic views summarizing distribution of viral integration sites are generated according to chromosome maps. It is free to browse and download data in Dr.VIS.
ANAT - Advanced Network Analysis Tool
Genome-scale screening studies are gradually accumulating a wealth of data on the putative involvement of hundreds of genes in various cellular responses or functions. A fundamental challenge is to chart out the molecular pathways that underlie these systems. ANAT (Advanced Network Analysis Tool) , is an all-in-one resource that provides access to up-to-date large-scale physical association data in several organisms, advanced algorithms for network reconstruction, and a number of tools for exploring and evaluating the obtained network models
GWAS central database
GWAS Central (previously the Human Genome Variation database of Genotype-to-Phenotype information) is a database of summary level findings from genetic association studies, both large and small. We actively gather datasets from public domain projects, and encourage direct data submission from the community.
GWAS Central is built upon a basal layer of Markers that comprises all known SNPs and other variants from public databases such as dbSNP and the DBGV. Allele and genotype frequency data, plus genetic association significance findings, are added on top of the Marker data, and organised the same way that investigations are reported in typical journal manuscripts. Critically, no individual level genotypes or phenotypes are presented in GWAS Central – only group level aggregated (summary level) data. The largest unit in a data submission is a Study, which can be thought of as being equivalent to one journal article. This may contain one or more Experiments, one or more Sample Panels of test subjects, and one or more Phenotypes. Sample Panels may be characterised in terms of various Phenotypes, and they also may be combined and/or split into Assayed Panels. The Assayed Panels are used as the basis for reporting allele/genotype frequencies (in `Genotype Experiments`) and/or genetic association findings (in ‘Analysis Experiments’). Environmental factors are handled as part of the Sample Panel and Assayed Panel data structures.
GWAS Central is built upon a basal layer of Markers that comprises all known SNPs and other variants from public databases such as dbSNP and the DBGV. Allele and genotype frequency data, plus genetic association significance findings, are added on top of the Marker data, and organised the same way that investigations are reported in typical journal manuscripts. Critically, no individual level genotypes or phenotypes are presented in GWAS Central – only group level aggregated (summary level) data. The largest unit in a data submission is a Study, which can be thought of as being equivalent to one journal article. This may contain one or more Experiments, one or more Sample Panels of test subjects, and one or more Phenotypes. Sample Panels may be characterised in terms of various Phenotypes, and they also may be combined and/or split into Assayed Panels. The Assayed Panels are used as the basis for reporting allele/genotype frequencies (in `Genotype Experiments`) and/or genetic association findings (in ‘Analysis Experiments’). Environmental factors are handled as part of the Sample Panel and Assayed Panel data structures.
Integrated Microbial Genomes- Education Site
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| Image by TheEverlastingFallout via Flickr |
Gene Expression Atlas update--a value-added database of microarray and sequencing-based functional genomics experiments.
The database supports 19 species, which contains expression data measured for 19 014 biological conditions in 136 551 assays from 5598 independent studies.
Galaxy DNA-analysis software is now available 'in the cloud'
Galaxy is an open, web-based platform for data intensive biomedical research. Whether on the free public server or your own instance, you can perform, reproduce, and share complete analyses.
OpenHelix: Tutorials and resources
Access over 100 tutorial suites on web-based bioinformatics and genomics resources
- Quickly learn how to use a resource when you need it.
- Save time teaching a resource with prepared training materials
- Know you'll be using the most proven-effective training available
- Have the confidence you have the best, most updated information
- Have piece of mind you are using materials created by experts
About - DAnCER - Wodak Lab: Disease Annotated Chromatin Epigenetic Resource
Epigenetics plays a key role in DNA replication, transcription and repair, and its disruption is implicated in the development of many forms of cancer and other diseases. As a result, there is now a growing number of projects dedicated to the study of chromatin modification - a crucial component of epigenetic processes. Similarly to other cellular processes, chromatin modification is carried out by groups of physically interacting proteins, and anomalies in protein interactions often lead to disease phenotypes. Yet there remains a dearth of public databases and analysis tools that explore the relationship between chromatin machinery and human disease, especially in the context of protein-interaction networks. DAnCER's goal is to fill this gap. I
EGAN: Exploratory Gene Association Networks. Leverage organic intelligence.
EGAN is a software tool that allows a bench biologist to visualize and interpret the results of high-throughput exploratory assays in an interactive hypergraph of genes, relationships (protein-protein interactions, literature co-occurrence, etc.) and meta-data (annotation, signaling pathways, etc.). EGAN provides comprehensive, automated calculation of meta-data coincidence (over-representation, enrichment) for user- and assay-defined gene lists, and provides direct links to web resources and literature (NCBI Entrez Gene, PubMed, KEGG, Gene Ontology, iHOP, Google, etc.).
The Cardiac Organellar Protein Atlas Knowledgebase
The COPa knowledgebase is a resource of proteome biology configured specially for cardiovascular investigators. This project is developed under NHLBI proteomics center program with the partnership of Beijing Genomics Institute (BGI), European Bioinformatics Institute , Royal Institute of Technology (KTH), The Scripps Research Institute (TSRI), the Zhejiang University (ZJU) and UCLA. We hope it will serve as a useful tool for advancing cardiovascular biology and medicine.
The innovations in proteome biology offer unprecedented opportunities towards translational medicine. Advancing cardiovascular medicine requires an understanding of cardiac function at the systems level but with sufficient molecular details at the same time. Proteomics technologies are large scale in nature and their datasets come in various forms. The integration of these resources inspires innovative insights and bridges data-driven discoveries with hypothesis-driven investigations. The effective and comprehensive characterization of proteome biology holds the promise to advance cardiovascular medicine.
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