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http://proportal.mit.edu/

ProPortal is a database containing genomic, metagenomic, transcriptomic and field data for the marine cyanobacterium Prochlorococcus. Our goal is to provide a source of cross-referenced data across multiple scales of biological organization--from the genome to the ecosystem--embracing the full diversity of ecotypic variation within this microbial taxon, its sister group, Synechococcus and phage that infect them. The site currently contains the genomes of 13 Prochlorococcus strains, 11 Synechococcus strains and 28 cyanophage strains that infect one or both groups. Cyanobacterial and cyanophage genes are clustered into orthologous groups that can be accessed by keyword search or through a genome browser. Users can also identify orthologous gene clusters shared by cyanobacterial and cyanophage genomes. Gene expression data for Prochlorococcus ecotypes MED4 and MIT9313 allow users to identify genes that are up or downregulated in response to environmental stressors. In addition, the transcriptome in synchronized cells grown on a 24-h light-dark cycle reveals the choreography of gene expression in cells in a ''natural'' state. Metagenomic sequences from the Global Ocean Survey from Prochlorococcus, Synechococcus and phage genomes are archived so users can examine the differences between populations from diverse habitats. Finally, an example of cyanobacterial population data from the field is included.

Proper citation: ProPortal (RRID:SCR_006112) Copy   

•   Source: SciCrunch Registry

http://humanmetabolism.org/

A comprehensive biochemical knowledge-base on human metabolism, this community-driven, consensus metabolic reconstruction integrates metabolic information from five different resources: * Recon 1, a global human metabolic reconstruction (Duarte et al, PNAS, 104(6), 1777-1782, 2007) * EHMN, Edinburgh Human Metabolic Network (Hao et al., BMC Bioinformatics 11, 393, 2010) * HepatoNet1, a liver metabolic reconstruction (Gille et al., Molecular Systems Biology 6, 411, 2010), * Ac/FAO module, an acylcarnitine/fatty acid oxidation module (Sahoo et al., Molecular bioSystems 8, 2545-2558, 2012), * a human small intestinal enterocytes reconstruction (Sahoo and Thiele, submitted). Additionally, more than 370 transport and exchange reactions were added, based on a literature review. Recon 2 is fully semantically annotated (Le Nov��re, N. et al. Nat Biotechnol 23, 1509-1515, 2005) with references to persistent and publicly available chemical and gene databases, unambiguously identifying its components and increasing its applicability for third-party users. Here you can explore the content of the reconstruction by searching/browsing metabolites and reactions. Recon 2 predictive model is available in the Systems Biology Markup Language format.

Proper citation: Recon x (RRID:SCR_006345) Copy   

•   Source: SciCrunch Registry

http://www.wwpdb.org/

Public global Protein Data Bank archive of macromolecular structural data overseen by organizations that act as deposition, data processing and distribution centers for PDB data. Members are: RCSB PDB (USA), PDBe (Europe) and PDBj (Japan), and BMRB (USA). This site provides information about services provided by individual member organizations and about projects undertaken by wwPDB. Data available via websites of its member organizations.

Proper citation: Worldwide Protein Data Bank (wwPDB) (RRID:SCR_006555) Copy   

•   Source: SciCrunch Registry

http://arabidopsis.med.ohio-state.edu

An information resource of Arabidopsis promoter sequences, transcription factors and their target genes that contains three databases. *AtcisDB consists of approximately 33,000 upstream regions of annotated Arabidopsis genes (TAIR9 release) with a description of experimentally validated and predicted cis-regulatory elements. *AtTFDB contains information on approximately 1,770 transcription factors (TFs). These TFs are grouped into 50 families, based on the presence of conserved domains. *AtRegNet contains 11,355 direct interactions between TFs and target genes. They provide free download of Arabidopsis thaliana cis-regulatory database (AtcisDB) and transcription factor database (AtTFDB).

Proper citation: Arabidopsis Gene Regulatory Information Server (RRID:SCR_006928) Copy   

•   Source: SciCrunch Registry

http://www.agbase.msstate.edu/

A curated, open-source, web-accessible resource for functional analysis of agricultural plant and animal gene products. Our long-term goal is to serve the needs of the agricultural research communities by facilitating post-genome biology for agriculture researchers and for those researchers primarily using agricultural species as biomedical models. AgBase provides tools designed to assist with the analysis of proteomics data and tools to evaluate experimental datasets using the GO. Additional tools for sequence analysis are also provided. We use controlled vocabularies developed by the Gene Ontology (GO) Consortium to describe molecular function, biological process, and cellular component for genes and gene products in agricultural species. AgBase will also accept annotations from any interested party in the research communities. AgBase develops freely available tools for functional analysis, including tools for using GO. We appreciate any and all questions, comments, and suggestions. AgBase uses the NCBI Blast program for searches for similar sequences. And the Taxonomy Browser allows users to find the NCBI defined taxon ID for or taxon name for different organisms.

Proper citation: AgBase (RRID:SCR_007547) Copy   

•   Source: SciCrunch Registry

http://www.biocheminfo.org/klotho/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. A database of biochemical compound information. All files are available for download, and all entries are cataloged by accession number. Klotho is part of a larger attempt to model biological processes, beginning with biochemistry.

Proper citation: Klotho: Biochemical Compounds Declarative Database (RRID:SCR_007714) Copy   

•   Source: SciCrunch Registry

http://www.broad.mit.edu/annotation/fungi/fgi/

Produces and analyzes sequence data from fungal organisms that are important to medicine, agriculture and industry. The FGI is a partnership between the Broad Institute and the wider fungal research community, with the selection of target genomes governed by a steering committee of fungal scientists. Organisms are selected for sequencing as part of a cohesive strategy that considers the value of data from each organism, given their role in basic research, health, agriculture and industry, as well as their value in comparative genomics.

Proper citation: Fungal Genome Initiative (RRID:SCR_003169) Copy   

•   Source: SciCrunch Registry

http://alchemy.sourceforge.net/

ALCHEMY is a genotype calling algorithm for Affymetrix and Illumina products which is not based on clustering methods. Features include explicit handling of reduced heterozygosity due to inbreeding and accurate results with small sample sizes. ALCHEMY is a method for automated calling of diploid genotypes from raw intensity data produced by various high-throughput multiplexed SNP genotyping methods. It has been developed for and tested on Affymetrix GeneChip Arrays, Illumina GoldenGate, and Illumina Infinium based assays. Primary motivations for ALCHEMY''s development was the lack of available genotype calling methods which can perform well in the absence of heterozygous samples (due to panels of inbred lines being genotyped) or provide accurate calls with small sample batches. ALCHEMY differs from other genotype calling methods in that genotype inference is based on a parametric Bayesian model of the raw intensity data rather than a generalized clustering approach and the model incorporates population genetic principles such as Hardy-Weinberg equilibrium adjusted for inbreeding levels. ALCHEMY can simultaneously estimate individual sample inbreeding coefficients from the data and use them to improve statistical inference of diploid genotypes at individual SNPs. The main documentation for ALCHEMY is maintained on the sourceforge-hosted MediaWiki system. Features * Population genetic model based SNP genotype calling * Simultaneous estimation of per-sample inbreeding coefficients, allele frequencies, and genotypes * Bayesian model provides posterior probabilities of genotype correctness as quality measures * Growing number of scripts and supporting programs for validation of genotypes against control data and output reformating needs * Multithreaded program for parallel execution on multi-CPU/core systems * Non-clustering based methods can handle small sample sets for empirical optimization of sample preparation techniques and accurate calling of SNPs missing genotype classes ALCHEMY is written in C and developed on the GNU/Linux platform. It should compile on any current GNU/Linux distribution with the development packages for the GNU Scientific Library (gsl) and other development packages for standard system libraries. It may also compile and run on Mac OS X if gsl is installed.

Proper citation: ALCHEMY (RRID:SCR_005761) Copy   

•   Source: SciCrunch Registry

http://www.sgn.cornell.edu/bulk/input.pl?modeunigene

Allows users to download Unigene or BAC information using a list of identifiers or complete datasets with FTP., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Sol Genomics Network - Bulk download (RRID:SCR_007161) Copy   

•   Source: SciCrunch Registry

http://www.nber.org/papers/h0038

A dataset to advance the study of life-cycle interactions of biomedical and socioeconomic factors in the aging process. The EI project has assembled a variety of large datasets covering the life histories of approximately 39,616 white male volunteers (drawn from a random sample of 331 companies) who served in the Union Army (UA), and of about 6,000 African-American veterans from 51 randomly selected United States Colored Troops companies (USCT). Their military records were linked to pension and medical records that detailed the soldiers������?? health status and socioeconomic and family characteristics. Each soldier was searched for in the US decennial census for the years in which they were most likely to be found alive (1850, 1860, 1880, 1900, 1910). In addition, a sample consisting of 70,000 men examined for service in the Union Army between September 1864 and April 1865 has been assembled and linked only to census records. These records will be useful for life-cycle comparisons of those accepted and rejected for service. Military Data: The military service and wartime medical histories of the UA and USCT men were collected from the Union Army and United States Colored Troops military service records, carded medical records, and other wartime documents. Pension Data: Wherever possible, the UA and USCT samples have been linked to pension records, including surgeon''''s certificates. About 70% of men in the Union Army sample have a pension. These records provide the bulk of the socioeconomic and demographic information on these men from the late 1800s through the early 1900s, including family structure and employment information. In addition, the surgeon''''s certificates provide rich medical histories, with an average of 5 examinations per linked recruit for the UA, and about 2.5 exams per USCT recruit. Census Data: Both early and late-age familial and socioeconomic information is collected from the manuscript schedules of the federal censuses of 1850, 1860, 1870 (incomplete), 1880, 1900, and 1910. Data Availability: All of the datasets (Military Union Army; linked Census; Surgeon''''s Certificates; Examination Records, and supporting ecological and environmental variables) are publicly available from ICPSR. In addition, copies on CD-ROM may be obtained from the CPE, which also maintains an interactive Internet Data Archive and Documentation Library, which can be accessed on the Project Website. * Dates of Study: 1850-1910 * Study Features: Longitudinal, Minority Oversamples * Sample Size: ** Union Army: 35,747 ** Colored Troops: 6,187 ** Examination Sample: 70,800 ICPSR Link: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06836

Proper citation: Early Indicators of Later Work Levels Disease and Death (EI) - Union Army Samples Public Health and Ecological Datasets (RRID:SCR_008921) Copy   

•   Source: SciCrunch Registry

http://www.geosamples.org/

Sample Catalog and Registry for the International Geo Sample Number. SESAR catalogs and preserves sample metadata profiles, and provides access to the sample catalog via the Global Sample Search.

Proper citation: System for Earth Sample Registration (RRID:SCR_002222) Copy   

•   Source: SciCrunch Registry

http://nsidc.org/agdc/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 2, 2025. Archives and distributes Antarctic glaciological and cryospheric system data collected by the U.S. Antarctic Program. The Data Catalog contains data sets collected by individual investigators and products assembled from many different PI data sets, published literature, and other sources. The catalog provides useful compilations of important geophysical parameters, such as accumulation rate or ice velocity. The NSF OPP Guidelines and Award Conditions for Scientific Data state that PIs should submit data collected as a result of their OPP grant to a designated data center as soon as possible, but no later than two years after the data are collected.

Proper citation: Antarctic Glaciological Data Center (RRID:SCR_002219) Copy   

•   Source: SciCrunch Registry

http://www.morphbank.net/

An NSF supported image repository of over 374,000 high-resolution photographs of approximately 4,000 species for research and education, used largely but not exclusively in the area of biodiversity research. Images can be annotated by users and browsed by specimen, view, taxonomy, location, collection, or annotation.

Proper citation: MorphBank (RRID:SCR_003147) Copy   

•   Source: SciCrunch Registry

http://cmr.jcvi.org/tigr-scripts/CMR/CmrHomePage.cgi

Database of all of the publicly available, complete prokaryotic genomes. In addition to having all of the organisms on a single website, common data types across all genomes in the CMR make searches more meaningful, and cross genome analysis highlight differences and similarities between the genomes. CMR offers a wide variety of tools and resources, all of which are available off of our menu bar at the top of each page. Below is an explanation and link for each of these menu options. * Genome Tools: Find organism lists as well as summary information and analyses for selected genomes. * Searches: Search CMR for genes, genomes, sequence regions, and evidence. * Comparative Tools: Compare multiple genomes based on a variety of criteria, including sequence homology and gene attributes. SNP data is also found under this menu. * Lists: Select and download gene, evidence, and genomic element lists. * Downloads: Download gene sequences or attributes for CMR organisms, or go to our FTP site. * Carts: Select genome preferences from our Genome Cart or download your Gene Cart genes. The Omniome is the relational database underlying the CMR and it holds all of the annotation for each of the CMR genomes, including DNA sequences, proteins, RNA genes and many other types of features. Associated with each of these DNA features in the Omniome are the feature coordinates, nucleotide and protein sequences (where appropriate), and the DNA molecule and organism with which the feature is associated. Also available are evidence types associated with annotation such as HMMs, BLAST, InterPro, COG, and Prosite, as well as individual gene attributes. In addition, the database stores identifiers from other centers such as GenBank and SwissProt, as well as manually curated information on each genome or each DNA molecule including website links. Also stored in the Omniome are precomputed homology data, called All vs All searches, used throughout the CMR for comparative analysis.

Proper citation: JCVI CMR (RRID:SCR_005398) Copy   

•   Source: SciCrunch Registry

http://www.vistrails.org/

Open-source scientific workflow and provenance management system that provides support for simulations, data exploration and visualization. It was designed to manage these rapidly-evolving workflows. VisTrails has a comprehensive provenance infrastructure that maintains detailed history information about the steps followed and data derived in the course of an exploratory task: VisTrails maintains provenance of data products, of the workflows that derive these products and their executions. This information is persisted as XML files or in a relational database, and it allows users to navigate workflow versions in an intuitive way, to undo changes but not lose any results, to visually compare different workflows and their results, and to examine the actions that led to a result. It also enables a series operations and user interfaces that simplify workflow design and use, including the ability to create and refine workflows by analogy and to query workflows by example. VisTrails supports the creation and execution of workflows. It allows the combination of loosely-coupled resources, specialized libraries, grid and Web services. The released version comes with support for several packages including, VTK, Image Magick, Web Services, and pylab. You can also download packages contributed by users, as well as create your own packages/modules. Workflows can be run interactively, through the VisTrails GUI, or in batch using a VisTrails server. VisTrails is written in Python and it uses the multi-platform Qt library for its user interface. It runs on Mac, Linux and Windows. Provenance-rich results derived by VisTrails can be included in LaTeX, Wiki, Microsoft Word and PowerPoint documents.

Proper citation: VisTrails (RRID:SCR_006261) Copy   

•   Source: SciCrunch Registry

http://www.ibioseminars.org/

iBioSeminars offers: * Free, on-demand lectures: Many universities/colleges have limited access to high profile leaders in biological research. Our goal is to add 15-20 seminars per year, of similar quality to outstanding lectures that are currently in this library. Access, through web streaming or download, is completely free-of-charge. * Targeting a broad audience: iBioSeminars start with an extended introduction, making them accessible to non-specialists and students, and then progress to cover current research. Senior scientists and students can view and enjoy these lectures. * Education: iBioSeminars are being used by undergraduate and graduate teachers to augment their classroom material. We have now added an education component to this web site (including lecture notes, questions/answers and short video clips for teaching). * International communication: iBioSeminars have viewers in 115 countries and they are being internally promoted in several countries as an educational tool and scientific resource. * Goodwill: Lecturers generously donate their time to prepare these lectures. The project, largely funded by HHMI, is a grass roots efforts with time invested by several individuals at UCSF, HHMI and ASCB.

Proper citation: iBioSeminars (RRID:SCR_005848) Copy   

•   Source: SciCrunch Registry

http://treebase.org/treebase-web/

Repository of phylogenetic information, specifically user-submitted phylogenetic trees and the data used to generate them. TreeBASE accepts all kinds of phylogenetic data (e.g., trees of species, trees of populations, trees of genes) representing all biotic taxa. Data in TreeBASE are exposed to the public if they are used in a publication that is in press or published in a peer-reviewed scientific journal, book, conference proceedings, or thesis. Data used in publications that are in preparation or in review can be submitted to TreeBASE but will not be available to the public until they have passed peer review.

Proper citation: TreeBASE (RRID:SCR_005688) Copy   

•   Source: SciCrunch Registry

http://vmd.vbi.vt.edu/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 15, 2013. Database covering a range of plant pathogenic oomycetes, fungi and bacteria primarily those under study at Virginia Bioinformatics Institute. The data comes from different sources and has genomes of 3 oomycetes pathogens: Phytophthora sojae, Phytophthora ramorum and Hyaloperonospora arabidopsidis. The genome sequences (95 MB for P.sojae and 65 MB for P.ramorum) were annotated with approximately 19,000 and approximately 16,000 gene models, respectively. Two different statistical methods were used to validate these gene models, Fickett''''s and a log-likelihood method. Functional annotation of the gene models is based on results from BlastX and InterProScan screens. From the InterProScan results, putative functions to 17,694 genes in P.sojae and 14,700 genes in P.ramorum could be assigned. An easy-to-use genome browser was created to view the genome sequence data, which opens to detailed annotation pages for each gene model. A community annotation interface is available for registered community members to add or edit annotations. There are approximately 1600 gene models for P.sojae and approximately 700 models for P.ramorum that have already been manually curated. A toolkit is provided as an additional resource for users to perform a variety of sequence analysis jobs.

Proper citation: VMD (RRID:SCR_004905) Copy   

•   Source: SciCrunch Registry

http://www.plexdb.org/index.php

PLEXdb (Plant Expression Database) is a unified gene expression resource for plants and plant pathogens. PLEXdb is a genotype to phenotype, hypothesis building information warehouse, leveraging highly parallel expression data with seamless portals to related genetic, physical, and pathway data. The integrated tools of PLEXdb allow investigators to use commonalities in plant biology for a comparative approach to functional genomics through use of large-scale expression profiling data sets.

Proper citation: PLEXdb - Plant Expression Database (RRID:SCR_006963) Copy   

•   Source: SciCrunch Registry

http://www.digitalfishlibrary.org/index.php

A database of 3D magnetic resonance (MRI) images of fish accessible to scientists, educators and the general public via the web. The Marine Vertebrate Collection at the Scripps Institution of Oceanography provides the majority of the DFL specimens.

Proper citation: Digital Fish Library (RRID:SCR_008338) Copy   

•   Source: SciCrunch Registry