Curator Dashboard

An integrated environment designed to support protein sequence and structure analysis on the web.

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• SciCrunch
• 14 years ago - by Anonymous

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.

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• SciCrunch
• 14 years ago - by Anonymous

A web tool, based on a heuristic transformation of the original global pairwise and local pairwise alignment algorithms, offers objective alignments for transmembrane protein sequences. hPATM takes advantage of the information offered by the knowledge of the position of transmembrane segmets, by experiment or prediction. The heuristic approach may reveal similarities between diverge sequences with low percentages of identity and similarity. The produced alignments, based on common structural scaffolds derived by the transmembrane segments of the sequence, can be used to spot conserved non-transmembrane segments or as a basis for the production of 3-D models via homology modelling. The hPAFAG algorithm is based on the heuristic transformation of the Needleman & Wunsch and Smith & Waterman algorithms, featuring affine gap penalties. The heuristic transformation is based on two extra features: * a heuristic bonus, added to the score when two amino acids that belong to transmembrane segmens are aligned. * a heuristic gap penalty, substracted from the score when a gap is opened in a transmembrane segment. This way transmembrane segments are anchored (not by force, but by more strict alignment) together, allowing the pairwise alignment to focus on non-transmembrane segments. This web server offers a friendly interface for the hPATM command line version. The algorithm was implemented in PERL and the source code of the command line version is available on request by the authors.

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• SciCrunch
• 14 years ago - by Anonymous

A publicly accessible, relational database of human G-Proteins and their interactions with human GPCRs and Effectors. Advanced data integration techniques make Human-gpDB very rich in context since all of the bioentities are linked to a rich variety of external data sources. High quality visualization methods make the networks more informative and the extraction of information easier. Human-gpDB is currently a very useful tool for drug targeting investigation. The sequences of G-Proteins and GPCRs are classified according to a hierarchy of different classes, families and sub-families, whereas the Effectors sequences are classified in families, subfamilies and types, based on extensive literature search. The classification of GPCRs follows the IUPHAR classification, while the Effectors classification is a unique feature and is based on their function. The database currently holds information about 713 human GPCRs, 36 human G-Proteins and 99 human Effectors. The collection of the information about the interactions between these molecules was done manually and the current status of Human-gpDB reveals information about 1663 connections between GPCRs and G-Proteins and 1618 connections between G-Proteins and Effectors.

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• SciCrunch
• 14 years ago - by Anonymous

A relational database of Lepidoptera chorion proteins. The proteinaceous Lepidopteran chorions are used in our lab, as a model system towards unraveling the routes and rules of formation of natural protective amyloids. Therefore, we constructed LepChorionDB a relational database, containing all Lepidoptera chorion proteins identified to date. Lepidoptera chorion proteins can be classified in two major protein families, A and B. This classification was based on multiple sequence alignments of conserved key residues, in the central domain of, well characterized, silkmoth chorion proteins. These alignments were used to build Hidden Markov Models in order to search various DataBases. This work was a collaboration of the Department of Cell Biology and Biophysics, University of Athens and the Centre of Immunology & Transplantation Biomedical Research Foundation, Academy of Athens.

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• SciCrunch
• 14 years ago - by Anonymous

A database of Beta-barrel outer membrane proteins from Gram-negative bacteria. The web interface of OMPdb offers the user the ability not only to view the available data, but also to submit advanced queries for text search within the database''s protein entries or run BLAST searches against the database. The most up-to-date version of the database (as well as all past versions) can be downloaded in various formats (flat text, XML format or raw FASTA sequences). For constructing OMPdb, multiple freely accessible resources were combined and a detailed literature search was performed. The classification of OMPdb''s protein entries into families is based mainly on structural and functional criteria. Information included in the database consists of sequence data, as well as annotation for structural characteristics (such as the transmembrane segments), literature references and links to other public databases, features that are unique worldwide. Along with the database, a collection of profile Hidden Markov Models that were shown to be characteristic for Beta-barrel outer membrane proteins was also compiled. This set, when used in combination with our previously developed algorithms (PRED-TMBB, MCMBB and ConBBPRED) will serve as a powerful tool in matters of discrimination and classification of novel Beta-barrel proteins and whole-genome analyses., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

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• SciCrunch
• 14 years ago - by Anonymous

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.

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• SciCrunch
• 14 years ago - by Anonymous

Provides standardized vocabulary of phenotypic abnormalities encountered in human disease. Structured and controlled vocabulary for phenotypic features encountered in human hereditary and other disease. HPO is being developed in collaboration with members of OBO Foundry (Open Biological and Biomedical Ontologies), and logical definitions for HPO terms are being developed using PATO and a number of other ontologies including FMA, GO, ChEBI, and MPATH.

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• SciCrunch
• 14 years ago - by Anonymous

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.

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• SciCrunch
• 14 years ago - by Anonymous

A Java based web application, which combines the results of methods that predict the location of transmembrane segments in protein sequences into a joint prediction histogram. Clearly, the joint prediction algorithm, produces superior quality results than individual prediction schemes.

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• SciCrunch
• 14 years ago - by Anonymous

A system of cascading neural networks that classifies any protein, given its amino acid sequence alone, into one of four possible classes: membrane, globular, fibrous, mixed.

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• SciCrunch
• 14 years ago - by Anonymous

An ontology written in OWL 2 DL to enable the metadata properties of the DataCite Metadata Kernel Specification version 2.2 (http://test.datacite.org/schema/meta/kernel-2.2/index.html) to be described in RDF. This version of the DataCite Ontology has been completely revised and significantly expanded to permit accurate mapping of this new version of the DataCite Metadata Kernel Specification to RDF.

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• SciCrunch
• 14 years ago - by Anonymous

Software package that provides quantitative variant callers for detecting subclonal mutations in ultra-deep (>=100x coverage) sequencing experiments. The algorithm is used for a comparative setup with a control experiment of the same loci and uses a beta-binomial model and a likelihood ratio test to discriminate sequencing errors and subclonal SNVs (single nucleotide variants).

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• SciCrunch
• 13 years ago - by Anonymous

Raw data from various QTL (quantitative trait loci) studies using rodent inbred line crosses. Data are available in the .csv format used by R/qtl and pseudomarker programs. In some cases analysis scripts and/or results are posted to accompany the data. These data are provided as a courtesy to the genetic mapping community and may be used for purposes of developing or testing new analysis methods or software and for meta-analysis of quantitative traits. The authors of the datasets retain individual ownership of the data. As a courtesy to the authors, please alert them in advance of any publications that result from reanalysis of these data or obtain permission prior to redistribution of data or results. In all data sets and files, the marker locations have been translated to Cox build 37 coordinates unless otherwise stated. Please consider contributing your data to the QTL Archive.

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• SciCrunch
• 14 years ago - by Anonymous

A portal of online studies that encourage community participation to tackle the most challenging problems in neuropsychiatry, including attention-deficit / hyperactivity disorder, schizophrenia, and bipolar disorder. Our approach is to engage the community and try to recruit tens of thousands of people to spend an hour of their time on our site. You folks will provide data in both brain tests and questionnaires, as well as DNA, and in return, we will provide some information about your brain and behavior. You will also be entered to win amazon.com gift cards. While large collaborative efforts were made in genetics in order to discover the secrets of the human genome, there are still many mysteries about the behaviors that are seen in complex neuropsychiatric syndromes and the underlying biology that gives rise to these behaviors. We know that it will require studying tens of thousands of people to begin to answer these questions. Having you, the public, as a research partner is the only way to achieve that kind of investment. This site will try to reach that goal, by combining high-throughput behavioral assessment using questionnaires and game-like cognitive tests. You provide the data and then we will provide information and feedback about why you should help us achieve our goals and how it benefits everyone in the world. We believe that through this online study, we can better understand memory and attention behaviors in the general population and their genetic basis, which will in turn allow us to better characterize how these behaviors go awry in people who suffer from mental illness. In the end, we hope this will provide better, more personalized treatment options, and ultimately prevention of these widespread and extremely debilitating brain diseases. We will use the data we collect to try to identify the genetic basis for memory and impulse control, for example. If we can achieve this goal, maybe we can then do more targeted research to understand how the biology goes awry in people who have problems with cognition, including memory and impulse control, like those diagnosed with ADHD, Schizophrenia, Bipolar Disorder, and Autism Spectrum Disorders. By participating in our research, you can learn about mental illness and health and help researchers tackle these complex problems. We can''t do it without your help.

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• SciCrunch
• 14 years ago - by Anonymous

A JAVA-based computer application that serves as a workbench for genome-wide analysis through visual interaction. GeneViTo offers an inspectional view of genomic functional elements, concerning data stemming both from database annotation and analysis tools for an overall analysis of existing genomes. The application deals with various experimental information concerning both DNA and protein sequences (derived from public sequence databases or proprietary data sources) and meta-data obtained by various prediction algorithms, classification schemes or user-defined features. Interaction with a Graphical User Interface (GUI) allows easy extraction of genomic and proteomic data referring to the sequence itself, sequence features, or general structural and functional features. Emphasis is laid on the potential comparison between annotation and prediction data in order to offer a supplement to the provided information, especially in cases of poor annotation, or an evaluation of available predictions. Moreover, desired information can be output in high quality JPEG image files for further elaboration and scientific use. GeneViTo has already been applied to visualize the genomes of two microbial organisms: the bacterion Chlamydia trachomatis and the archaeon Methanococcus jannaschii. The application is compatible with Linux or Windows ME-2000-XP operating systems, provided that the appropriate Java Runtime Environment (Java 1.4.1) is already installed in the system.

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• SciCrunch
• 14 years ago - by Anonymous

Public research university in Nottingham, United Kingdom. It was founded as University College Nottingham in 1881, and was granted a royal charter in 1948.

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• SciCrunch
• 12 years ago - submitted by Stephen Larson

A visualization hub displaying sequencing data from the Roadmap Epigenomics project. It hosts high volume of tracks from ENCODE and Roadmap Epigenomics projects, supports multiple organisms, visualizes chromatin-interaction data (e.g. Hi-C), performs gene set view, gene plot, and many others. All delivered on the web at high performance.

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• SciCrunch
• 14 years ago - by Anonymous

Software tool for visualizing and interacting with whole-genome datasets. Browser hosts Human Epigenome Atlas data produced by Roadmap Epigenomics project, but its use of advanced, multi-resolution data formats and its user-friendly interface make it possible for investigators to upload and visualize their own data as custom tracks. Developed and maintained by Epigenome Informatics Group at Washington University in St. Louis.

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• SciCrunch
• 14 years ago - by Anonymous

A clustering and visualization tool that enables the interactive exploration of genome-wide data, with a specialization in epigenomics data. Spark is also available as a service within the Epigenome toolset of the Genboree Workbench. The approach utilizes data clusters as a high-level visual guide and supports interactive inspection of individual regions within each cluster. The cluster view links to gene ontology analysis tools and the detailed region view connects to existing genome browser displays taking advantage of their wealth of annotation and functionality.

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• SciCrunch
• 14 years ago - by Anonymous