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https://protein.mpiib-berlin.mpg.de/cgi-bin/pdbs/2d-page/extern/index.cgi

The Proteome 2D-PAGE Database system for microbial research is a curated database for storing and investigating proteomics data. Software tools are available and for data submission, please contact the Database Curator. Established at the Max Plank Institution for Infection Biology, this system contains four interconnected databases: i.) 2D-PAGE Database: Two dimensional electrophoresis (2-DE) and mass spectrometry of diverse microorganisms and other organisms. This database currently contains 4971 identified spots and 1228 mass peaklists in 44 reference maps representing experiments from 24 different organisms and strains. The data were submitted by 84 Submitters from 24 Institutes and 12 nations. It also contains various software tools that are important in formatting and analyzing gels and mass peaks; software include: *TopSpot: Scanning the gel, editing the spots and saving the information *Fragmentation: Fragmentation of the gel image into sections *MS-Screener: Perl script to compare the similarity of MALDI-PMF peaklists *MS-Screener update: MS-Screener can be used to compare mass spectra (MALDI-MS(/MS) as well as ESI-MS/MS spectra) on the basis of their peak lists (.dta, .pkm, .pkt, or .txt files), to recalibrate mass spectra, to determine and eliminate exogenous contaminant peaks, and to create matrices for cluster analyses. *GelCali: Online calibration of the Mr- and pI-axis of 2-DE gels with mathematical regression methods ii.)Isotope Coded Affinity Tag (ICAT)-LC/MS database: Isotope Coded Affinity Tag (ICAT)-LC/MS data for Mycobacterium tuberculosis strain BCG versus H37Rv. iii.) FUNC_CLASS database: Functional classification of diverse microorganism. This database also integrates genomic, proteomic, and metabolic data. iv.) DIFF database: Presentation of differently regulated proteins obtained by comparative proteomic experiments using computerized gel image analysis.

Proper citation: Proteome 2D-PAGE Database (RRID:SCR_001678) Copy   

•   Source: SciCrunch Registry

http://videolectures.net/

Award-winning free and open access educational video lectures repository. The lectures are given by distinguished scholars and scientists at the most important and prominent events like conferences, summer schools, workshops and science promotional events from many fields of Science. The portal is aimed at promoting science, exchanging ideas and fostering knowledge sharing by providing high quality didactic contents not only to the scientific community but also to the general public. All lectures, accompanying documents, information and links are systematically selected and classified through the editorial process taking into account also users' comments.

Proper citation: VideoLectures.NET (RRID:SCR_001972) Copy   

•   Source: SciCrunch Registry

http://mips.gsf.de/genre/proj/yeast/index.jsp

The MIPS Comprehensive Yeast Genome Database (CYGD) aims to present information on the molecular structure and functional network of the entirely sequenced, well-studied model eukaryote, the budding yeast Saccharomyces cerevisiae. In addition, the data of various projects on related yeasts are used for comparative analysis.

Proper citation: CYGD - Comprehensive Yeast Genome Database (RRID:SCR_002289) Copy   

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

A novel algorithm for low-complexity region detection and selective masking. The algorithm is based on multiple-pass Smith-Waterman comparison of the query sequence against twenty homopolymers with infinite gap penalties. The output of the algorithm is both the masked query sequence for further analysis, e.g. database searches, as well as the regions of low complexity.

Proper citation: CAST (RRID:SCR_000628) Copy   

•   Source: SciCrunch Registry

https://juaml.github.io/julearn

Software library of easy testing ML models directly from pandas DataFrames, while keeping the flexibility of using scikit-learn’s models.

Proper citation: Julearn (RRID:SCR_024881) Copy   

•   Source: SciCrunch Registry

http://starnet.mssm.edu/

Web interactive browser to visualize data and perform gene set enrichment analysis along with gene and SNP lookup. Web interface used to query STARNET datasets and downstream analysis which includes RNAseq from 7 tissues: blood, free internal mammary artery (MAM), atherosclerotic aortic root (AOR), subcutaneous fat (SF), visceral abdominal fat (VAF), skeletal muscle (SKLM), and liver (LIV). Paired SNP genotyping data is included and utilized for tissue expression quantitative trait loci (eQTL), CAD heritability (H2), co-expression networks and gene regulatory networks.

Proper citation: STARNET (RRID:SCR_025238) Copy   

•   Source: SciCrunch Registry

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

A computer software that utilizes an initial definition of transmembrane segments to predict the topology of transmembrane proteins from their sequence. It uses position-specific statistical information for amino acid residues which belong to putative non-transmembrane segments derived from a statistical analysis of non-transmembrane regions of membrane proteins stored in the SwissProt database. Its accuracy compares well with that of other popular existing methods.

Proper citation: orienTM (RRID:SCR_006218) Copy   

•   Source: SciCrunch Registry

http://xldb.fc.ul.pt/biotools/rebil/goa/

A tool for assisting the GO annotation of UniProt entries by linking the GO terms present in the uncurated annotations with evidence text automatically extracted from the documents linked to UniProt entries. Platform: Online tool

Proper citation: GoAnnotator (RRID:SCR_005792) Copy   

•   Source: SciCrunch Registry

http://gopubmed.org/web/gopubmed/

A web server which allows users to explore PubMed search results with the Gene Ontology, a hierarchically structured vocabulary for molecular biology. GoPubMed submits a user''''s keywords to PubMed, retrieves the abstracts, detects Gene Ontology terms in the abstracts, displays the subset of Gene Ontology relevant to the original query, and allows the user to browse through the ontology displaying associated papers and their GO annotation. Platform: Online tool

Proper citation: GoPubMed (RRID:SCR_005823) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/expressionprofiler/

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. The EP:GO browser is built into EBI's Expression Profiler, a set of tools for clustering, analysis and visualization of gene expression and other genomic data. With it, you can search for GO terms and identify gene associations for a node, with or without associated subnodes, for the organism of your choice.

Proper citation: Expression Profiler (RRID:SCR_005821) Copy   

•   Source: SciCrunch Registry

http://athina.biol.uoa.gr/PRED-TMR2/

A web server that classifies proteins into two classes from their sequences alone: the membrane protein class and the non-membrane protein class. This may be important in the functional assignment and analysis of open reading frames (ORF''s) identified in complete genomes and, especially, those ORF''s that correspond to proteins with unknown function. The network has a simple hierarchical feed-forward topology and a limited number of neurons which makes it very fast. By using only information contained in 11 protein sequences, the method was able to identify, with 100% accuracy, all membrane proteins with reliable topologies collected from several papers in the literature. Applied to a test set of 995 globular, water-soluble proteins, the neural network classified falsely 23 of them in the membrane protein class (97.7% of correct assignment). The method was also applied to the complete SWISS-PROT database with considerable success and on ORF''s of several complete genomes. The neural network developed was associated with the PRED-TMR algorithm (Pasquier,C., Promponas,V.J., Palaios,G.A., Hamodrakas,J.S. and Hamodrakas,S.J., 1999) in a new application package called PRED-TMR2.

Proper citation: PRED-TMR2 (RRID:SCR_006205) Copy   

•   Source: SciCrunch Registry

http://athina.biol.uoa.gr/PRED-TMR/

A web server that predicts transmembrane domains in proteins using solely information contained in the sequence itself. The algorithm refines a standard hydrophobicity analysis with a detection of potential termini (edges, starts and ends) of transmembrane regions. This allows both to discard highly hydrophobic regions not delimited by clear start and end configurations and to confirm putative transmembrane segments not distinguishable by their hydrophobic composition. The accuracy obtained on a test set of 101 non homologous transmembranes proteins with reliable topologies compares well with that of other popular existing methods. Only a slight decrease in prediction accuracy was observed when the algorithm was applied to all transmembrane proteins of the SwissProt database (release 35).

Proper citation: PRED-TMR (RRID:SCR_006203) Copy   

•   Source: SciCrunch Registry

http://www.alzheimer-europe.org/

A non-governmental organization aimed at raising awareness of all forms of dementia by creating a common European platform through co-ordination and co-operation between Alzheimer organizations throughout Europe. Alzheimer Europe is also a source of information on all aspects of dementia.

Proper citation: Alzheimer Europe (RRID:SCR_003802) Copy   

•   Source: SciCrunch Registry

https://github.com/INCF/csa

Software tool for description of connectivity in small and large scale neuronal network models. It provides operators to form more complex sets of connections from simpler ones and also provides parameterization of such sets. Can be used as component of neuronal network simulators or other tools.

Proper citation: Connection-set algebra (RRID:SCR_017397) Copy   

•   Source: SciCrunch Registry

http://www.brenda-enzymes.org/

Database for functional enzyme and ligand-related information maintained as part of the German ELIXIR Node. Provides advanced query systems, evaluation tools, and various visualization options for the detailed assessment of enzyme properties. Enzyme data in BRENDA are classified according to the Enzyme Commission (EC) nomenclature of IUBMB.

Proper citation: BRENDA (RRID:SCR_002997) Copy   

•   Source: SciCrunch Registry

http://www.ensembl.org/

Collection of genome databases for vertebrates and other eukaryotic species with DNA and protein sequence search capabilities. Used to automatically annotate genome, integrate this annotation with other available biological data and make data publicly available via web. Ensembl tools include BLAST, BLAT, BioMart and the Variant Effect Predictor (VEP) for all supported species.

Proper citation: Ensembl (RRID:SCR_002344) Copy   

•   Source: SciCrunch Registry

http://search.driver.research-infrastructures.eu/

Data infrastructure project that merged with OpenAIRE. Cohesive, robust and flexible, pan-European infrastructure for digital repositories, offering sophisticated services and functionalities for researchers, administrators and the general public. Access the network of freely accessible digital repositories with content across academic disciplines with over 3,500,000 scientific publications, found in journal articles, dissertations, books, lectures, reports, etc., harvested regularly from more than 295 repositories, from 38 countries. DRIVER has established a network of relevant experts and Open Access repositories. DRIVER-II will consolidate these efforts and transform the initial testbed into a fully functional, state-of-the art service, extending the network to a larger confederation of repositories. It aims to optimize the way the e-Infrastructure is used to store knowledge, add value to primary research data and information making secondary research more effective, provide a valuable asset for industry, and help bridging research and education. The objectives of DRIVER-II, the second phase of the project, include efforts to expand, enrich, and strengthen the results of DRIVER, in the following areas: * strategic geographic and community expansion by means of the DRIVER confederation * establish a robust, scalable repository infrastructure accompanied by an open source software package D-Net * broader coverage of content through the use of enhanced publications * advanced end-user functionality to support scientific exploration of complex digital objects * larger outreach and advocacy programs * continued repository support * guidelines for interoperability in the larger European digital library community

Proper citation: Digital Repository Infrastructure Vision for European Research (RRID:SCR_002752) Copy   

•   Source: SciCrunch Registry

http://degradome.uniovi.es

A database of human, chimpanzee, mouse, and rat proteases and protease inhibitors, as well as as the growing number of hereditary diseases caused by mutations in protease genes. Analysis of the human and mouse genomes has allowed us to annotate 581 human, 580 chimpanzee, 667 mouse, and 655 rat protease genes. Proteases are classified in five different classes according to their mechanism of catalysis. Proteases are a diverse and important group of enzymes representing >2% of the human, chimpanzee, mouse and rat genomes. This group of enzymes is implicated in numerous physiological processes. The importance of proteases is illustrated by the existence of 99 different hereditary diseases due to mutations in protease genes. Furthermore, proteases have been implicated in multiple human pathologies, including vascular diseases, rheumatoid arthritis, neurodegenerative processes, and cancer. During the last ten years, our laboratory has identified and characterized more than 60 human protease genes. Due to the importance of proteolytic enzymes in human physiology and pathology, we have recently introduced the concept of Degradome, as the complete repertoire of proteases expressed by a tissue or organism. Thanks to the recent completion of the human, chimpanzee, mouse, and rat genome sequencing projects, we were able to analyze and compare for the first time the complete protease repertoire in those mammalian organisms, as well as the complement of protease inhibitor genes. This webpage also contains the Supplementary Material of Human and mouse proteases: a comparative genomic approach Nat Rev Genet (2003) 4: 544-558, Genome sequence of the brown Norway rat yields insights into mammalian evolution Nature (2004) 428: 493-521, A genomic analysis of rat proteases and protease inhibitors Genome Res. (2004) 14: 609-622, and Comparative genomic analysis of human and chimpanzee proteases Genomics (2005) 86: 638-647.

Proper citation: Mammalian Degradome Database (RRID:SCR_007624) Copy   

•   Source: SciCrunch Registry

http://www.informatics.jax.org/home/recombinase

Curated data about all recombinase-containing transgenes and knock-ins developed in mice providing a comprehensive resource delineating known activity patterns and allows users to find relevant mouse resources for their studies.

Proper citation: Recombinase (cre) Activity (RRID:SCR_006585) Copy   

•   Source: SciCrunch Registry

http://hcsquared.eu/home

HC2 is an EU funded project that aims to promote, support and help define future lines of research in Human Computer Confluence (HCC). HCC is the study of the intersection of HCI, Cognitive Neuroscience, VR/AR, Presence, Pervasive Computing and how they can enable new forms of sensing, perception, interaction and understanding. In a sense it is the study of the disappearing interface. HCC, Human-Computer Confluence, is an ambitious research program studying how the emerging symbiotic relation between humans and computing devices can enable radically new forms of sensing, perception, interaction, and understanding. The horizontal character of HCC makes it a fascinating and fertile interdisciplinary field, but it can also compromise its growth, with researchers scattered across disciplines and groups worldwide. To address this we are building a community of HCC researchers. There are lots of ways you can join in. Add your name to the HCC Players Map, take advantage of our Exchange Program to work with colleagues at your favorite lab, sign up for our Summer School or just follow us on Twitter and LinkedIn to see what''s happening. In order to foster interdisciplinary research and promote HCC research we have set up an Exchange Program. Students that wish to apply for financial support from our Exchange Program should follow the steps provided. The Exchange Program is open to all graduate students (Masters and PhD). A maximum of 500 Euro support will be provided per student.

Proper citation: HC2: Human-Computer Confluence (RRID:SCR_005549) Copy   

•   Source: SciCrunch Registry