Tools   Select Another Resource Report Type

http://www.scienceexchange.com/facilities/agcenter-biotechnology-laboratory-lsu

The LSU AgCenter Biotechnology Laboratory (ABL) is a core facility that provides basic and applied research expertise to support researchers in the LSU system as well as those in other academic institutions and industry. The ABL was formed in 1998 to provide support to faculty in performing biomolecular research. In 2010, the ABL was merged with the Protein Facility in LSU''''s College of Basic Sciences. Today, the ABL consists of three units: the Protein Facility, the Plant Transformation Facility and the Animal Cell Culture Facility.

Proper citation: LSU AgCenter Biotechnology Laboratory (RRID:SCR_012536) Copy   

•   Source: SciCrunch Registry

http://www.scienceexchange.com/facilities/children-s-hospital-boston-intellectual-and-developmental-disabilities-research-center-molecular-genetics-core

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 8,2024. An Core facility

Proper citation: Childrens Hospital Boston Intellectual And Developmental Disabilities Research Center - Molecular Genetics Core (RRID:SCR_012414) Copy   

•   Source: SciCrunch Registry

https://www.unmc.edu/vcr/cores/vcr-cores/mspcf/index.html

MSPCF maintains and uses equipment for protein separation and imaging, as well as for sample preparation for mass spectrometry analysis. Offers range of bioinformatics tools for data mining and evaluation. Services include Protein Identification, Protein Interactome Analysis, Protein Post-translational Modifications, Quantitative Mass Spectrometry, Molecular Weight determination.

Proper citation: University of Nebraska Medical Center Mass Spectrometry and Proteomics Core Facility (RRID:SCR_012539) Copy   

•   Source: SciCrunch Registry

https://www.mri.psu.edu/materials-characterization-lab

Fully-staffed, open access, analytical research facility at Penn State's Materials Research Institute. Provided services include Surface Analysis (XPS, AFM, AES), Electron Microscopy (TEM, SEM, FIB, EPMA), X-ray Scattering (XRD and SAXS), Molecular Spectroscopy (FTIR, Raman, UV-VIs-NIR), Electrical Testing, Optical Microscopy, Thermal Analysis, Mechanical Testing, and Sample Preparation.

Proper citation: Pennsylvania State University Materials Characterization Lab Core Facility (RRID:SCR_012386) Copy   

•   Source: SciCrunch Registry

https://bcmb.franklin.uga.edu/bff

BFF consists of Fermentation Research Facility, Protein Purification Facility, Monoclonal Antibody Facility and Cell Culture Facility. Provides services covering wide range of biomanufacturing areas, protein expression, purification and antibody discovery.Provides equipment and expertise in biotechnological applications to academic and industry clients.

Proper citation: University of Georgia Bioexpression and Fermentation Core Facility (RRID:SCR_012421) Copy   

•   Source: SciCrunch Registry

http://athina.biol.uoa.gr/SCAR/

A web tool to create, display and manipulate structures of small molecules, proteins and DNA.

Proper citation: SCAR (RRID:SCR_006227) Copy   

•   Source: SciCrunch Registry

http://athina.biol.uoa.gr/bioinformatics/NON-RED/index.html

A web tool to select biological sequences from a given set, with similarity / homology less than a user-defined level. This web-based application takes as input a set of N sequences and outputs a set of sequences of user-determined redundancy. Initially, the algorithm runs an all-against-all BLAST alignment on the input data set and creates an NxN matrix of pairwise distances defined by the similarity percentages. In the next step, the algorithm removes the sequence with the largest number of neighbors, causing that sequence not to be counted as a neighbor of any other sequence during the next iterations. It then reassesses the number of neighbors of each sequence and repeats the previous step until the sequences left over have no more neighbors. The user can specify the similarity (%) threshold and the minimum coverage length of the alignments. Sequences with a similarity below the threshold or a smaller coverage than the minimum length are not considered to be neighbors.

Proper citation: NON-RED (RRID:SCR_006225) Copy   

•   Source: SciCrunch Registry

http://ncrad.iu.edu/

Cell repository for Alzheimer's disease that collects and maintains biological specimens and associated data. Its data is derived from large numbers of genetically informative, phenotypically well-characterized families with multiple individuals affected with Alzheimer's disease, as well as individuals for case-control studies.

Proper citation: National Cell Repository for Alzheimer's Disease (RRID:SCR_007313) Copy   

•   Source: SciCrunch Registry

http://athina.biol.uoa.gr/SecStr/

A tool to Predict the Secondary Structure of a protein from its amino acid sequence alone. The SecStr package uses six different secondary structure prediction methods (Nagano, Garnier et al., Burges et al., Chou and Fasman , Lim and Dufton and Hider). The results of those methods are combined into a Joint Prediction Histogram (JPH) as described by Hamodrakas, 1988 and Hamodrakas et al., 1982. As previously mentioned, the SecStr package contains computer programs making use of the secondary structure prediction methods of Nagano, Garnier et al., Burges et al., Chou and Fasman, Lim and Dufton and Hider. These programs were written in Fortran. The results of individual prediction methods are combined as described by Hamodrakas (1988), using a Perl program, to produce joint prediction histograms (JPH), for three types of secondary structure, which may be presented separately on a Java Applet. The output may be given either in text or graphics mode. For the latter a Java capable browser is required.

Proper citation: SecStr (RRID:SCR_006220) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.biol.uoa.gr/CW-PRED/

A web tool for the prediction of Cell Wall-Anchored Proteins in Gram+ Bacteria. Gram-positive bacteria have surface proteins that are often implicated in virulence. A group of extracellular proteins attached to the cell wall contains an LPXTG-like motif that is target for cleavage and covalent coupling to peptidoglycan by sortase enzymes. A new Hidden Markov Model (HMM), an extension to the HMM model from Litou et al., http://www.ncbi.nlm.nih.gov/pubmed/18464329, was developed for predicting the LPXTG and LPXTG-like cell-wall proteins of Gram-positive bacteria. An analysis of 177 completely sequenced genomes has been performed as well. We identified in total 1456 cell-wall proteins, from which 1283 have the LPXTG motif, 39 the NPXTG motif, 53 have the LPXTA and 81 the LAXTG motif.

Proper citation: CW-PRED (RRID:SCR_006188) Copy   

•   Source: SciCrunch Registry

http://omicslab.genetics.ac.cn/GOEAST/

Gene Ontology Enrichment Analysis Software Toolkit (GOEAST) is a web based software toolkit providing easy to use, visualizable, comprehensive and unbiased Gene Ontology (GO) analysis for high-throughput experimental results, especially for results from microarray hybridization experiments. The main function of GOEAST is to identify significantly enriched GO terms among give lists of genes using accurate statistical methods. Compared with available GO analysis tools, GOEAST has the following unique features: * GOEAST supports analysis for data from various resources, such as expression data obtained using Affymetrix, illumina, Agilent or customized microarray platforms. GOEAST also supports non-microarray based experimental data. The web-based feature makes GOEAST very user friendly; users only have to provide a list of genes in correct formats. * GOEAST provides visualizable analysis results, by generating graphs exhibiting enriched GO terms as well as their relationships in the whole GO hierarchy. * Note that GOEAST generates separate graph for each of the three GO categories, namely biological process, molecular function and cellular component. * GOEAST allows comparison of results from multiple experiments (see Multi-GOEAST tool). The displayed color of each GO term node in graphs generated by Multi-GOEAST is the combination of different colors used in individual GOEAST analysis. Platform: Online tool

Proper citation: GOEAST - Gene Ontology Enrichment Analysis Software Toolkit (RRID:SCR_006580) Copy   

•   Source: SciCrunch Registry

https://www.mdanderson.org/research/departments-labs-institutes/programs-centers/michale-e-keeling-center-for-comparative-medicine-and-research/national-research-resources-program.html

SMBRR maintains the only self-sustaining national research resource of laboratory-born squirrel monkeys, their tissues and other biological materials, as well as the expertise to carry out research on this animal. Scientists with NIH grants utilize squirrel monkeys to study many diseases that threaten human health including Alzheimer's disease and other disorders of the central nervous system, drug addiction, malaria, and viral diseases. Center that carries out research on squirrel monkey biology and its research uses. It meets the needs of the biomedical research community in three ways: providing national resource for laboratory-born squirrel monkeys, having active research component that continues to add new information about the biology of the squirrel monkey with a particular emphasis on reproduction and colony management, and acts as a source of expertise for squirrel monkey biology, management and husbandry.

Proper citation: Squirrel Monkey Breeding and Research Resource (RRID:SCR_006291) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://mousespinal.brain-map.org/about.html

Platform for exploring spinal cord at cellular and molecular levels. Map of gene expression for adult and juvenile mouse spinal cord. Provides map of normal mouse when used to compare gene expression in diseased or injury models. Interactive database of gene expression mapped across all anatomic segments of mouse spinal cord at postnatal days 4 and 56. Indexed set of images based on RNA in situ hybridization data, searchable and sortable by gene, age, expression, cervical, thoracic, lumbar, sacral, and coccygeal segments.

Proper citation: Allen Mouse Spinal Cord Atlas (RRID:SCR_007418) Copy   

•   Source: SciCrunch Registry

http://cbl-gorilla.cs.technion.ac.il/

A tool for identifying and visualizing enriched GO terms in ranked lists of genes. It can be run in one of two modes: * Searching for enriched GO terms that appear densely at the top of a ranked list of genes or * Searching for enriched GO terms in a target list of genes compared to a background list of genes.

Proper citation: GOrilla: Gene Ontology Enrichment Analysis and Visualization Tool (RRID:SCR_006848) Copy   

•   Source: SciCrunch Registry

http://webclu.bio.wzw.tum.de/profcom/

Profiling of Complex Functionality (ProfCom) is a web-based tool for the functional interpretation of a gene list that was identified to be related by experiments. A trait which makes ProfCom a unique tool is an ability to profile enrichments of not only available Gene Ontology (GO) terms but also of complex function. A complex function is constructed as Boolean combination of available GO terms. The complex functions inferred by ProfCom are more specific in comparison to single terms and describe more accurately the functional role of genes. Platform: Online tool

Proper citation: ProfCom - Profiling of complex functionality (RRID:SCR_005797) Copy   

•   Source: SciCrunch Registry

http://tmbeta-genome.cbrc.jp/TMFunction/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 29,2025. Database of functional residues in alpha-helical and beta-barrel membrane proteins. Each protein is identified with its name and source alongwith the Uniprot code. The protein data bank (PDB) codes are also given for available proteins. Different methods and experimental parameters, for example, affinity, dissociation constant, IC50, activity etc. are given in the database. Further, the database provides the numerical experimental value for each residue (or mutant) in a protein. The experimental data are collected from the literature both by searching the journals as well as with the keyword search at PUBMED. In addition, complete reference is given with journal citation and PMID number. TNFunction is cross-linked with the sequence database, Uniprot, structural database, PDB, and literature database, PubMed. The WWW interface enables users to search data based on various terms with different display options for outputs.

Proper citation: TM Function Database (RRID:SCR_007058) Copy   

•   Source: SciCrunch Registry

http://www.compbio.dundee.ac.uk/gotcha/gotcha.php

GOtcha provides a prediction of a set of GO terms that can be associated with a given query sequence. Each term is scored independently and the scores calibrated against reference searches to give an accurate percentage likelihood of correctness. These results can be displayed graphically. Why is GOtcha different to what is already out there and why should you be using it? * GOtcha uses a method where it combines information from many search hits, up to and including E-values that are normally discarded. This gives much better sensitivity than other methods. * GOtcha provides a score for each individual term, not just the leaf term or branch. This allows the discrimination between confident assignments that one would find at a more general level and the more specific terms that one would have lower confidence in. * The scores GOtcha provides are calibrated to give a real estimate of correctness. This is expressed as a percentage, giving a result that non-experts are comfortable in interpreting. * GOtcha provides graphical output that gives an overview of the confidence in, or potential alternatives for, particular GO term assignments. The tool is currently web-based; contact David Martin for details of the standalone version. Platform: Online tool

Proper citation: GOtcha (RRID:SCR_005790) Copy   

•   Source: SciCrunch Registry

http://bioapps.sabanciuniv.edu/enzyminer/

EnzyMiner automatically identifies the PubMed abstracts that contain information on the impact of a protein level mutation on the stability or the activity of a given enzyme. For querying EnzyMiner, please choose an enzyme from the list and specify if you are interested in disease related abstracts or non-disease related abstracts. For disease related abstracts, the mutation list and direct links to the abstracts will be displayed. For those abstracts that are related to non-diseases, in addition to having the mutation list, the abstracts are also categorized into two groups. These two groups determine whether the mutation has an effect on the enzyme''s stability or functionality. If your target enzyme is not in the list, please write the enzyme name to the query box. We will run the EnzyMiner for the desired enzyme and add the results to our database. EnzyMiner has been developed by Computational Biology Lab of Sabanci University.

Proper citation: Enzyminer. (RRID:SCR_006241) Copy   

•   Source: SciCrunch Registry

http://panoga.sabanciuniv.edu/

A web server to devise functionally important pathways through the identification of single nucleotide polymorphism (SNP)-targeted genes within these pathways. The strength of the methodology stems from its multidimensional perspective, where evidence from the following five resources is combined: (i) genetic association information obtained through GWAS, (ii) SNP functional information, (iii) protein-protein interaction network, (iv) linkage disequilibrium and (v) biochemical pathways.

Proper citation: PANOGA (RRID:SCR_006242) Copy   

•   Source: SciCrunch Registry