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http://www.functionalneurogenesis.com/blog/

A blog focusing on the function of adult neurogenesis in the dentate gyrus of the hippocampus, including discussion of scientific research papers, methods and protocols, and other trends or observations about the field.

Proper citation: Functional Neurogenesis (RRID:SCR_008830) Copy   

•   Source: SciCrunch Registry
  

http://cushing.med.yale.edu/gsdl/cgi-bin/library

The images in this collection are derived from high resolution scans of glass 3.25 X 4 inch lantern slides that were part of a large collection of slides covering his years at the Rockefeller University and Yale University School of Medicine. These selected images were scanned by James D. Jamieson, M.D., Ph.D., a student of Palade. The images also include some of the earliest electron micrographs taken by collaborators of George Palade both at the Rockefeller University (1945 - 1973) and at Yale (1973 - 1990). They include micrographs taken by Professor Marilyn Farquhar, Ph.D., whose studies elucidated the function of the glomerular basement membrane in renal filtration. There are 5 ways to find information in this collection: search for particular words that appear in the text by clicking the Search button; browse documents by Title by clicking the Titles button; browse documents by Subject by clicking the Subjects button; browse documents by Creator by clicking the Creators button, and browse documents by References by clicking the References button. Sponsors: This collection is the result of a collaboration between James D. Jamieson, M.D., Ph.D., Professor, Dept. of Cell Biology, and Arthur R. Belanger, OBE, Systems Manager, Harvey Cushing/John Hay Whitney Medical Library, both at the Yale University School of Medicine.

Proper citation: George E. Palade EM Slide Collection. (RRID:SCR_008675) Copy   

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http://recombineering.ncifcrf.gov/

Recombineering (recombination-mediated genetic engineering) is a powerful method for fast and efficient construction of vectors for subsequent manipulation of the mouse genome or for use in cell culture experiments. It is also an efficient way of manipulating the bacterial genome directly. Recombineering is a method based on homologous recombination in E. Coli using recombination proteins provided from ? phage. Our bacterial strains contain a defective ? prophage inserted into the bacterial genome. The phage genes of interest, exo, bet, and gam, are transcribed from the ?PL promoter. This promoter is repressed by the temperature-sensitive repressor cI857 at 32C and derepressed (the repressor is inactive) at 42C. When bacteria containing this prophage are kept at 32C no recombination proteins are produced. However, after a brief (15 minutes) heat-shock at 42C a sufficient amount of recombination proteins are produced. exo is a 5''-3'' exonuclease that creates single-stranded overhangs on introduced linear DNA. bet protects these overhangs and assists in the subsequent recombination process. gam prevents degradation of linear DNA by inhibiting E. Coli RecBCD protein. Linear DNA (PCR product, oligo, etc.) with sufficient homology in the 5'' and 3'' ends to a target DNA molecule already present in the bacteria (plasmid, BAC, or the bacterial genome itself) can be introduced into heat-shocked and electrocompetent bacteria using electroporation. The introduced DNA will now be modified by exo and bet and undergo homologous recombination with the target molecule. The method is so efficient that co-electroporation of a supercoiled plasmid and a linear piece of DNA into heat-shocked, electrocompetent bacteria will work as well.

Proper citation: Recombineering Information (RRID:SCR_008556) Copy   

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http://biobehavioural.blogspot.com/

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 6, 2016. Biobehavioral blog on research and medicine as a continuum from biological mechanisms to behavioural phenomena., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Biobehavioral (RRID:SCR_008710) Copy   

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http://mips.helmholtz-muenchen.de/funcatDB/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 19, 2019. The Functional Catalogue is an annotation scheme for the functional description of proteins of prokaryotic and eukaryotic origin. Taking into account the broad and highly diverse spectrum of known protein functions, the FunCat consists of 28 main functional categories (or branches) that cover general fields like cellular transport, metabolism and cellular communication/signal transduction. The main branches exhibit a hierarchical, tree like structure with up to six levels of increasing specificity. In total, the FunCat version 2.1 includes 1362 functional categories. This general concept was retained since the annotation of the Saccharomyces cerevisiae genome with only 4 revisions and later on also proved to be well suited for the annotation of genomes from different domains of life (Ruepp et al. 2004). The present and previous versions as well as a version mapping file of the FunCat and annotation data of our core projects can be downloaded via FTP. The MIPS Functional Catalogue Database provides a search tool to browse and search the Functional Categories including the FunCat Number, description, EC number, GO number or keywords associated with the categories. All FunCat annotated proteins and the amount of Co-annotated-FunCats can be retrieved starting with a specific category in a selected organism. A statistical survey of the functional distribution of a given set of genes/entries, e. g. a set of genes with up-regulated expression under a certain condition can be retrieved.

Proper citation: MIPS FunCat (RRID:SCR_008709) Copy   

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http://www.nordgen.org/index.php/en/content/view/full/467

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 18,2023.

Proper citation: Nordic Genetic Resource Center (RRID:SCR_008706) Copy   

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http://www.cnio.es/ES/grupos/plantillas/presentacion.asp?grupo=50004308

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. The need to use human neoplastic tissue under ideal conditions is currently of particular importance due to the development molecular pathology techniques that allow large-scale studies of genetic expression that are also of clinical significance. The Tumour Bank Network (TBN), instigated and coordinated by the Molecular Pathology Programme (MMP) aims to respond to this need by the promoting of Tumour Banks in Spanish hospitals. This will be achieved through the application of homogeneous procedures for the collection, processing and storage of neoplastic and normal tissue samples in such a way as to make molecular studies possible, avoiding that avoid the intrinsic bias of multi-centre studies possible. These Hospital Tumour Banks are based within the Pathology Departments of the collaborating Hospitals, that are interconnected through a computer-based network. In this way, each Centre''s tissue remains in the Hospital itself, thereby playing a key role in the development of the welfare, teaching and research activities within the Hospital. At the same time, it represents a tool to encourage of multi-hospital cancer research and of cooperation between basic and clinical researchers, constituting important collaboration between biomedical disciplines. The design does not correspond to a Central Tumour Bank, but that of a cooperative and coordinated Network of Hospital Banks, based on simple, homogeneous and optimal tissue treatment protocols. This Network is promoted by the Centro Nacional de Investigaciones Oncologicas (CNIO), which thereby undertakes the work of coordinating the network, using and maintaining the database, adhering to quality control. The aim of the CNIO's TBN is to acquire neoplastic and control non-neoplastic material of all types of malignant neoplasias, in the form of tissue fixed in formalin and paraffin embedded, of samples that are unfixed or frozen according to conventional methods as set out in Annexe 1 and even, exceptionally as fresh tissue. When other types of samples are required to carry out a specific project, the central office of the TBN will draw up a protocol with the group leading the project for the collection and maintenance of the tissue and clinicopathological data required for the proposed research. These protocols will be disseminated among the Associated Hospitals in order to gather the previously agreed number cases. Basic data surrounding the processing and preservation conditions for each case will be sent to the central office of the Bank, which under no circumstances will reveal the identity of the patient. Any Spanish cancer research team will be able to request tissue from the Tissue Bank Network. Absolute priority will be afforded to projects whose principal researcher belongs to one of the Associated Centres of the TNB, to other institutions with special agreements concerning the exchange of samples, and to the CNIO's researchers.

Proper citation: Spanish National Tumour Bank Network (RRID:SCR_008707) Copy   

•   Source: SciCrunch Registry
  

http://gump.qimr.edu.au/general/daleN/SNPSpD/

SNPSpD is a method of correcting for non-independance of single nucleotide polymorphisms (SNPs) in linkage disequilibrium (LD) with each other, on the basis of the spectral decomposition (SpD) of matrices of LD between SNP''s. Additionally, output from SNPSpD includes eigenvalues, principal-component coefficients, and factor loadings after varimax rotation, enabling the selection of a subset of SNPs that optimize the information in a genomic region.

Proper citation: Single Nucleotide Polymorphism Spectral Decomposition (SNPSpD) (RRID:SCR_008621) Copy   

•   Source: SciCrunch Registry
  

http://wwwmgs.bionet.nsc.ru/mgs/programs/panalyst/

WebProAnalyst provides web-accessible analysis for scanning the quantitative structure-activity relationships in protein families. It searches for a sequence region, whose substitutions are correlated with variations in the activities of a homologous protein set, the so-called activity modulating sites. WebProAnalyst allows users to search for the key physicochemical characteristics of the sites that affect the changes in protein activities. It enables the building of multiple linear regression and neural networks models that relate these characteristics to protein activities. WebProAnalyst implements multiple linear regression analysis, back propagation neural networks and the Structure-Activity Correlation/Determination Coefficient (SACC/SADC). A back propagation neural network is implemented as a two-layered network, one layer as input, the other as output (Rumelhart et al, 1986). WebProAnalyst uses alignment of amino acid sequences and data on protein activity (pK, Km, ED50, among others). The input data are the numerical values for the physicochemical characteristics of a site in the multiple alignment given by a slide window. The output data are the predicted activity values. The current version of WebProAnalyst handles a single activity for a single protein. The SACC/SADC may be defined as an estimate of the strongest multiple correlation between the physicochemical characteristics of a site in a multiple alignment and protein activities. The SACC/SADC coefficient makes possible the calculation of the possible highest correlation achievable for the quantitative relationship between the physicochemical properties of sites and protein activities. The SACC/SADC is a convenient means for an arrangement of positions by their functional significance. WebProAnalyst outputs a list of multiple alignment positions, the respective correlation values, also regression analysis parameters for the relationships between the amino acid physicochemical characteristics at these positions and the protein activity values.

Proper citation: Webproanalyst (RRID:SCR_008348) Copy   

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http://www.cmbi.ru.nl/GeneSeeker/

The GeneSeeker allows you to search across different databases simultaneously, given a known human genetic location and expression/phenotypic pattern. The GeneSeeker returns any found gene names which are located on the specified location and expressed in the specified tissue. To search for more expression location in one search, just enter them in the textbox for the expression location and separate them with logical operators (and, or, not). You can specify as many tissues as you want, the program starts 20 queries simultaneously, and then waits for a query to finish before starting another query, to keep server loads to a minimum. You can also search only for expression, just leave the cytogenetic location fields blank, and do the query. If you only want to look for one cytogenetic location, only fill in the first location field, and the GeneSeeker will search with only this one. Housekeeping genes , found in Swissprot can be excluded, or genes that are to be excluded can be specified. Human chromosome localizations are translated with an oxford-grid to mouse chromosome localizations, and then submitted to the Mgd. Sponsors: GeneSeeker is a service provided by the Centre for Molecular and Biomolecular Informatics (CMBI).

Proper citation: GeneSeeker (RRID:SCR_008347) Copy   

•   Source: SciCrunch Registry
  

http://bionot.askhermes.org/integrated/BioNot.uwm

Database of negated biomedical sentences in literature consisting of more than 32 million negated sentences. Negated sentences were detected using the algorithm described in - Shashank Agarwal, Hong Yu Biomedical negation scope detection with Conditional Random Fields Journal of the American Medical Informatics Association (JAMIA), 2010; 17:696-701. After entering your query in the search box (for example MeCP2 autism), the search results with the negated sentence and the sentences preceding and following the negated sentences are displayed. A link to the source of the sentence is also provided, which links to the article from which the negated sentence was extracted. BioNOT is no longer updated. Documented 2013.

Proper citation: BioNOT (RRID:SCR_008743) Copy   

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http://empai.iab.keio.ac.jp/

emPAI (exponentially modified protein abundance index), developed by Ishihama et al., is a measure to describe the protein composition in sample solutions. When the total protein amount in the sample is available, emPAI can be converted to the absolute amount of each protein in the sample. emPAI is derived from PAI, which is defined as the number of the observed peptides divided by the number of the observable peptides per protein. We recently found that log (PAI) had linear relationship to the protein amounts, and that emPAI, 10^(PAI)-1, was proportional to the protein amounts for whole cell lysate digested by trypsin. The accuracy of this method was within factor 5, similar or better than determination of abundance by protein staining

Proper citation: Exponentially Modified Protein Abundance Index (RRID:SCR_008616) Copy   

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http://openlibrary.org/

Open Library is a project of the non-profit Internet Archive, and is funded in part by a grant from the California State Library. They have a small team of fantastic programmers who have accomplished a lot, but we can''t do it alone! This is an Open project - the software is open, the data is open, the documentation is open, and the site is open. To build it, they need hundreds of millions of book records, a brand new database infrastructure for handling huge amounts of dynamic information, a wiki interface, multi-language support, and people who are willing to contribute their time, effort, and book data. To date, they have gathered about 30 million records (20 million are available through the site now), and more are on the way. They have built the database infrastructure and the wiki interface, and you can search millions of book records, narrow results by facet, and search across the full text of 1 million scanned books. Sponsors: Open Library is funded by a grant from the California State Library.

Proper citation: Open Library (RRID:SCR_008295) Copy   

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http://connectivity.brain-map.org/

Map of neural connections in mouse brain, built on an array of transgenic mice genetically engineered to target specific cell types. In addition to the connectivity data, information about the transgenic mouse lines and genetic tracers is available. Consists of high resolution 2-D projectivity image data that can be viewed side-by-side with the associated reference atlas and other reference datasets. Enables 3-D visualization and spatial/ontological search of connectivity models through a combination of manual and informatics analyses.

Proper citation: Allen Mouse Brain Connectivity Atlas (RRID:SCR_008848) Copy   

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http://dcv.uhnres.utoronto.ca/SCRIPDB/search/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 2, 2025. Database of chemicals and reactions inside of US patents (2001 - 2011). SCRIPDB provides the full original patent text, reactions and relationships described within any individual patent, in addition to the molecular files common to structural databases. The patent literature is a rich catalog of biologically relevant chemicals; many public and commercial molecular databases contain the structures disclosed in patent claims. However, patents are an equally rich source of metadata about bioactive molecules, including mechanism of action, disease class, homologous experimental series, structural alternatives, or the synthetic pathways used to produce molecules of interest. Unfortunately, this metadata is discarded when chemical structures are deposited separately in databases. SCRIPDB is a chemical structure database designed to make this metadata accessible. The SCRIPDB information is valuable in medical text mining, chemical image analysis, reaction extraction and in silico pharmaceutical lead optimization. SCRIPDB may be searched by exact chemical structure, substructure or molecular similarity and the results may be restricted to patents describing synthetic routes.

Proper citation: SCRIPDB (RRID:SCR_008922) Copy   

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http://lsid.tdwg.org/

A web based life sciences identifier (LSID) resolution service allows you to view the data and metadata of an LSID with a web browser. This service will display the metadata, formatted as a standard webpage, for any LSID.

Proper citation: LSID Web Resolver (RRID:SCR_009737) Copy   

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http://dnatraffic.ibb.waw.pl/

DNAtraffic database is dedicated to be an unique comprehensive and richly annotated database of genome dynamics during the cell life. DNAtraffic contains extensive data on the nomenclature, ontology, structure and function of proteins related to control of the DNA integrity mechanisms such as chromatin remodeling, DNA repair and damage response pathways from eight model organisms commonly used in the DNA-related study: Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Saccharomyces cerevisiae, Schizosaccharomyces pombe, Escherichia coli and Arabidopsis thaliana. DNAtraffic contains comprehensive information on diseases related to the assembled human proteins. Database is richly annotated in the systemic information on the nomenclature, chemistry and structure of the DNA damage and drugs targeting nucleic acids and/or proteins involved in the maintenance of genome stability. One of the DNAtraffic database aim is to create the first platform of the combinatorial complexity of DNA metabolism pathway analysis. Database includes illustrations of pathway, damage, protein and drug. Since DNAtraffic is designed to cover a broad spectrum of scientific disciplines it has to be extensively linked to numerous external data sources. Database represents the result of the manual annotation work aimed at making the DNAtraffic database much more useful for a wide range of systems biology applications. DNAtraffic database is freely available and can be queried by the name of DNA network process, DNA damage, protein, disease, and drug.

Proper citation: DNAtraffic (RRID:SCR_008886) Copy   

•   Source: SciCrunch Registry
  

http://bioinfo.au.tsinghua.edu.cn/MethCGI/MethCGI.html

MethCGI is a tool to predict the methylation status of CpG islands in the human brain, developed on the data from human brain DNA using support vector machine (SVM).

Proper citation: MethCGI (RRID:SCR_010565) Copy   

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http://www.danubianbiobank.de/

Not yet vetted by NIF curator

Proper citation: Danubian Biobank Consortium (RRID:SCR_010566) Copy   

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http://psb.kobic.re.kr/STAP/refinement/

STAP refinement of NMR Database is based the Statistical Torsion Angles Potentials to refine the NMR structure. It stored original solution NMR structures from the Protein Data Banks and our refined structures. Currently we carried out 2,405 refined NMR structure (until Sept 20, 2011). According to several studies, some nuclear magnetic resonance (NMR) structures are of lower quality, less reliable and less suitable for structural analysis than high-resolution X-ray crystallographic structures. STAP of NMR Refinement Database is a public database of 2405 refined NMR solution structures from the Protein Data Bank (PDB). A simulated annealing protocol was employed to obtain refined structures with target potentials, including the newly developed STAP. The refined database was extensively analyzed using various quality indicators from several assessment programs to determine the nuclear Overhauser effect (NOE) completeness, Ramachandran appearance, (1)-(2) rotamer normality, various parameters for protein stability and other indicators. Most quality indicators are improved in our protocol mainly due to the inclusion of the newly developed knowledge-based potentials. This database can be used by the NMR structure community for further development of research and validation tools, structure-related studies and modelling in many fields of research.

Proper citation: Statistical Torsional Angles Potentials of NMR Refinement Database (RRID:SCR_008917) Copy   

•   Source: SciCrunch Registry