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http://cmrm.med.jhmi.edu/cmrm/atlas/human_data/file/JHUtemplate_newuser.html

DTI white matter atlases with different data sources and different image processing. These include single-subject, group-averaged, B0 correction, processed atlases (White Matter Parcellation Map, Tract-probability maps, Conceptual difference between the WMPM and tract-probability maps), and linear or non-linear transformation for automated white matter segmentation. # Adam single-subject white matter atlas (old version): These are electronic versions of atlases published in Wakana et al, Radiology, 230, 77-87 (2004) and MRI Atlas of Human White Matter, Elsevier. ## Original Adam Atlas: 256 x 256 x 55 (FOV = 246 x 246 mm / 2.2 mm slices) (The original matrix is 96x96x55 (2.2 mm isotropic) which is zerofilled to 256 x 256 ## Re-sliced Adam Atlas: 246 x 246 x 121 (1 mm isotropic) ## Talairach Adam: 246 x 246 x 121 (1 mm isotropic) # New Eve single-subject white matter atlas: The new version of the single-subject white matter atlas with comprehensive white matter parcellation. ## MNI coordinate: 181 x 217 x 181 (1 mm isotropic) ## Talairach coordinate: 181 x 217 x 181 (1 mm isotropic) # Group-averaged atlases: This atlas was created from their normal DTI database (n = 28). The template was MNI-ICBM-152 and the data from the normal subjects were normalized by affine transformation. Image dimensions are 181x217x181, 1 mm isotropic. There are two types of maps. The first one is the averaged tensor map and the second one is probabilistic maps of 11 white matter tracts reconstructed by FACT. # ICBM Group-averaged atlases: This atlas was created from ICBM database. All templates follow Radiology convention. You may need to flip right and left when you use image registration software that follows the Neurology convention.

Proper citation: DTI White Matter Atlas (RRID:SCR_005279) Copy   

•   Source: SciCrunch Registry

http://blog.ketyov.com/

Bradley Voytek''''s blog is where he tries out new ideas. He will often be wrong, but that''''s the point. He is a Neuroscientist studying human cognition, neuroplasticity, and brain computer interfacing. Into really geeky stuff. World zombie neuroscience expert. Also runs brainSCANr.com with his wife, Jessica.

Proper citation: Oscillatory Thoughts (RRID:SCR_005481) Copy   

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http://bioapps.rit.albany.edu/MITOPRED/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. It predicts nuclear-encoded mitochondrial proteins from all eukaryotic species including plants. Prediction is based on the occurrence patterns of Pfam domains (version 16.0) in different cellular locations, amino acid composition and pI value differences between mitochondrial and non-mitochondrial locations. Additionally, you may download MITOPRED predictions for complete proteomes. Re-calculated predictions are instantly accessible for proteomes of Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila, Homo sapiens, Mus musculus and Arabidopsis species as well as all the eukaryotic sequences in the Swiss-Prot and TrEMBL databases. Queries, at different confidence levels, can be made through four distinct options: (i) entering Swiss-Prot/TrEMBL accession numbers; (ii) uploading a local file with such accession numbers; (iii) entering protein sequences; (iv) uploading a local file containing protein sequences in FASTA format. The Mitopred algorithm works based on the differences in the Pfam domain occurrence patters and amino acid composition differences in different cellular compartments. Location specific Pfam domains have been determined from the entire eukaryotic set of Swissprot database. Similarly, differences in the amino acid composition between mitochondrial and non-mitochondrial sequences were pre-calculated. This information is used to calculate location-specific amino acid weights that are used to calculate amino acid score. Similarly, pI average values of the N-terminal 25 residues in different cellular location were also determined. This knowledge-base is accessed by the program during execution.

Proper citation: mitopred (RRID:SCR_006135) Copy   

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https://www.youtube.com/user/iniusc

Videos uploaded to YouTube by the Laboratory of Neuro Imaging (LONI). The Laboratory of Neuro Imaging at UCLA strives to improve our understanding of the brain in health and disease. LONI is a leader in the development of advanced computational algorithms and scientific approaches for the comprehensive and quantitative mapping of brain structure and function.

Proper citation: Laboratory of Neuro Imaging - YouTube (RRID:SCR_005462) Copy   

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https://bioinformatics.oxfordjournals.org/content/21/4/557.full.pdf

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 18, 2016. MAP-O-MAT is a web-based server for automated linkage mapping of human polymorphic DNA markers. The server uses publicly available genotype data for over 15,000 markers. It facilitates the verification of order and map distances for custom mapping sets using genotype data from the CEPH database, and from the Marshfield, SNP Consortium and Rutgers linkage maps. The CRI-MAP program is used for likelihood calculations and some mapping algorithms, and physical map positions are provided from the human genome assembly.

Proper citation: MAP-O-MAT (RRID:SCR_008197) Copy   

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http://igs-server.cnrs-mrs.fr/mgdb/Rickettsia/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 18, 2016. Rickettsia are obligate intracellular bacteria living in arthropods. They occasionally cause diseases in humans. To understand their pathogenicity, physiologies and evolutionary mechanisms, RicBase is sequencing different species of Rickettsia. Up to now we have determined the genome sequences of R. conorii, R. felis, R. bellii, R. africae, and R. massiliae. The RicBase aims to organize the genomic data to assist followup studies of Rickettsia. This website contains information on R. conorii and R. prowazekii. A R. conorii and R. prowazekii comparative genome map is also available. Images of genome maps, dendrogram, and sequence alignment allow users to gain a visualization of the diagrams.

Proper citation: Rickettsia Genome Database (RRID:SCR_007102) Copy   

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http://neurocritic.blogspot.com/

The Neurocritic is a blog deconstructing the most sensationalistic recent findings in Human Brain Imaging, Cognitive Neuroscience, and Psychopharmacology. Born in West Virginia in 1980, The Neurocritic embarked upon a roadtrip across America at the age of thirteen with his mother. She abandoned him when they reached San Francisco and The Neurocritic descended into a spiral of drug abuse and prostitution. At fifteen, The Neurocritic''s psychiatrist encouraged him to start writing as a form of therapy.

Proper citation: Neurocritic (RRID:SCR_006528) Copy   

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http://ccg.vital-it.ch/snp2tfbs

Collection of text files providing specific annotations for human single nucleotide polymorphisms (SNPs), namely whether they are predicted to abolish, create or change the affinity of one or several transcription factor (TF) binding sites. Used to investigate the molecular mechanisms underlying regulatory variation in the human genome. SNP2TFBS is also accessible over a web interface, enabling users to view the information provided for an individual SNP, to extract SNPs based on various search criteria, to annotate uploaded sets of SNPs or to display statistics about the frequencies of binding sites affected by selected SNPs.

Proper citation: SNP2TFBS (RRID:SCR_016885) Copy   

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https://omicc.niaid.nih.gov

Community based, biologist friendly web platform for creating and meta analyzing annotated gene expression data compendia., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: OMiCC (RRID:SCR_016604) Copy   

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https://github.com/zuoxinian/CCS

Software tool for multimodal human brain imaging data analysis. Computational pipeline for discovery science of human brain connectomes at macroscale with multimodal magnetic resonance imaging technologies.

Proper citation: Connectome Computation System (RRID:SCR_017342) Copy   

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http://www.informatics.jax.org/homology.shtml

MGI contains homology information for mouse, human, rat, chimp, dog and other species. Complete set of human, chimpanzee, rhesus macaque, dog, cattle, rat, chicken, western clawed frog and zebrafish Homology Classes for mouse genes. Report includes Chromosome and EntrezGene and OMIM IDs. Report of Human and Mouse Homology Classes sorted by HomoloGene ID includes associated nucleotide and protein sequences, Chromosome and OMIM IDs. Report of Human and Mouse Homology with phenotype annotations. Several additional MGI reports are available, including those for Gene Ontology, Phenotypes and Nomenclature.

Proper citation: Vertebrate Homology (RRID:SCR_017517) Copy   

•   Source: SciCrunch Registry

https://anvilproject.org/

Portal to facilitate integration and computing on and across large datasets generated by NHGRI programs, as well as initiatives funded by National Institutes of Health or by other agencies that support human genomics research. Resource for genomic scientific community, that leverages cloud based infrastructure for democratizing genomic data access, sharing and computing across large genomic, and genomic related data sets. Component of federated data ecosystem, and is expected to collaborate and integrate with other genomic data resources through adoption of FAIR (Findable, Accessible, Interoperable, Reusable) principles, as their specifications emerge from scientific community. Will provide collaborative environment, where datasets and analysis workflows can be shared within consortium and be prepared for public release to broad scientific community through AnVIL user interfaces.

Proper citation: Analysis, Visualization, and Informatics Lab-space (AnVIL) (RRID:SCR_017469) Copy   

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https://portal.brain-map.org/atlases-and-data/rnaseq

Software tool to visualize and analyze transcriptomics data and transcriptomic cell types for mouse and human, all directly in web browser. To explore gene expression heatmap across cell types in datasets, search for genes of interest, explore tSNE visualization, colored by cell types or expression of genes of interest, visualize dataset’s sampling strategy to see how cells and nuclei were sampled across brain areas, cortical layer, and other dimensions, find cell type of interest in one visualization and see its characteristics in different visualization.Used for Allen Brain Map Cell Types Database to Browse Data: Human - Multiple Cortical Areas, and Mouse - Cortex and Hippocampus.

Proper citation: Transcriptomics Explorer (RRID:SCR_017567) Copy   

•   Source: SciCrunch Registry

https://kg.ebrains.eu/

Metadata management system built for EBRAINS. Multi modal metadata store which brings together information from different areas of Human Brain Project as well as from external partners. Graph database tracks linkage between experimental data and neuroscientific data science supporting more extensive data reuse and complex computational research.Supports rich terminologies, ontologies and controlled vocabularies. Built by design to support iterative elaborations of common standards and supports these by probabilistic suggestion and review systems.

Proper citation: EBRAINS Knowledge Graph (RRID:SCR_017612) Copy   

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https://scdevdb.deepomics.org/

Database for insights into single cell gene expression profiles during human developmental processes. Interactive database provides DE gene lists in each developmental pathway, t-SNE map, and GO and KEGG enrichment analysis based on these differential genes.

Proper citation: Single Cell Developmental Database (RRID:SCR_017546) Copy   

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http://circadb.hogeneschlab.org/

Database of mammalian circadian gene expression profiles. Works with link outs to Wikipedia, HomoloGene, Refseq, etc.. Open source database of circadian transcriptional profiles from time course expression experiments from mice and humans.

Proper citation: CircaDB (RRID:SCR_018078) Copy   

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http://cancer.case.edu/research/sharedresources/tissue/services/

A combined tissue bank and core facility which provides annotated human tissue samples for research purposes. The facility also offers high quality tissue procurement, tissue microarray, histology, immunohistochemistry, photomicroscopy, and laser capture microdissection services for both human and animal tissues to biomedical investigators conducting non-clinical research studies. The TPHC offers instruction to researchers on how to incorporate human tissue into research activities and how to work within the boundaries of patient confidentiality and other regulatory issues. The purpose of the TPHC is to provide tissue collection and processing services to intramural and extramural researchers studying cancer and other diseases. Normal, diseased, benign and malignant tissues are obtained, and matched normal adjacent tissues and tissues from different organ sites from the same donor can also be provided when available. Tissue samples are prepared according to user-specified protocols and can be fresh in a medium of choice, fixed in formalin, quick frozen in the vapor phase of liquid nitrogen or snap-frozen by plunging the sample into liquid nitrogen. Frozen tissues are held in the vapor phase of the liquid nitrogen. Tissues can also be embedded, cut and mounted on slides, and stained upon request. Tissue Microarray (TMA) services are offered for the design and construction of TMAs meeting specific project needs. Basic demographic data (age, race, gender) and histopathologic data from Surgical Pathology Reports are provided by the TPHC with the tissues.

Proper citation: Case Western Reserve Tissue Procurement and Histology Core Facility (RRID:SCR_005344) Copy   

•   Source: SciCrunch Registry

http://americaninstituteofstress.org/interviews/

From time to time the Editor of Health and Stress interviews leaders in the field of stress management on a variety of topics for inclusion in our publications. Some interviews are listed below. For a complete list of interviews and content, you must be a member of AIS and access the Archives.

Proper citation: American Institute of Stress Interviews (RRID:SCR_005420) Copy   

•   Source: SciCrunch Registry

http://publications.nigms.nih.gov/computinglife/

An NIGMS magazine that showcases the exciting ways that scientists are using the power of computers to expand our knowledge of biology and medicine. From text messaging friends to navigating city streets with GPS technology, we''re all living the computing life. But as we''ve upgraded from snail mail and compasses, so too have scientists. Computer advances now let researchers quickly search through DNA sequences to find gene variations that could lead to disease, simulate how flu might spread through your school and design three-dimensional animations of molecules that rival any video game. By teaming computers and biology, scientists can answer new and old questions that could offer insights into the fundamental processes that keep us alive and make us sick. This booklet introduces you to just some of the ways that physicists, biologists and even artists are computing life. Each section focuses on a different research problem, offers examples of current scientific projects and acquaints you with the people conducting the work. You can follow the links for online extras and other opportunities to learn aboutand get involved inthis exciting new interdisciplinary field.

Proper citation: NIGMS Computing Life (RRID:SCR_005850) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/Projects/D_rerio/zmp/

Create knockout alleles in protein coding genes in the zebrafish genome, using a combination of whole exome enrichment and Illumina next generation sequencing, with the aim to cover them all. Each allele created is analyzed for morphological differences and published on the ZMP site. Transcript counting is performed on alleles with a morphological phenotype. Alleles generated are archived and can be requested from this site through the Zebrafish International Resource Center (ZIRC). You may register to receive updates on genes of interest, or browse a complete list, or search by Ensembl ID, gene name or human and mouse orthologue.

Proper citation: ZMP (RRID:SCR_006161) Copy   

•   Source: SciCrunch Registry