Curator Dashboard

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 2,2025. G-SESAME contains a set of tools. They include: tools for measuring the semantic similarity of GO terms; tools for measuring the functional similarity of genes; and tools for clustering genes based on their GO term annotation information. Platform: Online tool, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

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• SciCrunch
• 15 years ago - by Anonymous

Focused on cell signalling pathways, provides access to reagents and services involving kinase and ubiquitin targets and associated substrates and interacting proteins. Provides expertise and assistance in projects development. Offers services for protein generation and antibody development.

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• SciCrunch
• 4 years ago - submitted by Edyta Vieth

Online GEne Essentiality database containing genes that were tested experimentally for essentiality and their features; it also provides a set of tools to systematically explore and analyze these data. The main purpose of this project is to better understand gene essentiality by facilitating the comparisons of the differences and similarities between essential and non-essential genes. This is achieved by collecting not only experimentally tested essential and non-essential genes, but also associated gene features such as expression profiles, duplication status, conservation across species, evolutionary origins and involvement in embryonic development. We focus on large-scale experiments and complement our data with text-mining results. Genes are organized into data sets according to their sources. Genes with variable essentiality status across data sets are tagged as conditionally essential, highlighting the complex interplay between gene functions and environments. Linked tools allow the user to compare gene essentiality among different gene groups, or compare features of essential genes to non-essential genes, and visualize the results. Why is it different from existing databases? * we included both essential and non-essential genes so that we could better understand the gene essentiality by comparing the similarities and differences between the two gene sets; * we compiled a list of features for each gene, including whether they are duplicates or involved in development, the number of other homologous genes in the same genome, as well as their earliest expression stages during development. These features are keys to understand the essentiality of genes; * we also provide a set of tools to explore our data and visualize the results. For example, users can simply divide genes into two groups according to whether they are duplicates, calculate the proportion of essential genes (PE%) in each group and then visualize the results in a bar plot; or they can classify genes into multiple groups according to their earliest expression stages during evolution, compare the essentiality of genes that were expressed earlier with those were latter, and plot the results in a line chart.

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• SciCrunch
• 15 years ago - by Anonymous

Source code that performs multiple alignment of peptidic sequences. It utilizes posterior decoding and a sequence-annealing alignment, instead of the traditional progressive alignment method.

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• SciCrunch
• 9 years ago - submitted by Isabella Froman

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 28,2025. Project mapping whole mouse brain connectivity using serial block face scanning electron microscopy (SBF-SEM) with a specially-designed whole-brain microtome (WBM). With any luck, the whole mouse brain will be mapped ultrastructurally in the near term, which will then open the door to more serious problems; reliable automated segmentation and circuit reconstruction. These will undoubtedly require advances in machine learning methods and their application. Connectomics Software and a Multiresolution Image Viewer (MIV) is also available.

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• SciCrunch
• 14 years ago - by Anonymous

Software that facilitates accurate extraction of text from PDF files of research articles for use in text mining applications. It is intended for both scientists and natural language processing (NLP) engineers interested in getting access to text within specific sections of research articles. The system extracts text blocks from PDF-formatted full-text research articles and classifies them into logical units based on rules that characterize specific sections. The LA-PDFText system focuses only on the textual content of the research articles. The current version of LA-PDFText is a baseline system that extracts text using a three-stage process: * identification of blocks of contiguous text * classification of these blocks into rhetorical categories * extraction of the text from blocks grouped section-wise.

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• SciCrunch
• 15 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented January 29, 2018.
From website: "Note that the eXpress software is also no longer being developed. We recommend you use kallisto instead." Kallisto can be found at http://pachterlab.github.io/kallisto/.

Software for streaming quantification for high-throughput DNA/RNA sequencing.
Can be used in any application where abundances of target sequences need to be estimated from short reads sequenced from them.

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• SciCrunch
• 13 years ago - by Anonymous

A database of genomic and protein data for Drosophila site-specific transcription factors.

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• SciCrunch
• 13 years ago - by Anonymous

A hidden Markov model (HMM) for predicting somatic loss of heterozygosity and allelic imbalance in whole tumour genome sequencing data.

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• SciCrunch
• 13 years ago - by Anonymous

A scalable software pipeline for whole genome resequencing analysis.

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• SciCrunch
• 13 years ago - by Anonymous

Database of microRNA target predictions and expression profiles. Target predictions are based on a development of the miRanda algorithm which incorporates current biological knowledge on target rules and on the use of an up-to-date compendium of mammalian microRNAs. MicroRNA expression profiles are derived from a comprehensive sequencing project of a large set of mammalian tissues and cell lines of normal and disease origin. This website enables users to explore: * The set of genes that are potentially regulated by a particular microRNA. * The implied cooperativity of multiple microRNAs on a particular mRNA. * MicroRNA expression profiles in various mammalian tissues. The web resource provides users with functional information about the growing number of microRNAs and their interaction with target genes in many species and facilitates novel discoveries in microRNA gene regulation. The microRNA Target Detection Software, miRanda, is an algorithm for finding genomic targets for microRNAs. This algorithm has been written in C and is available as an open-source method under the GPL., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

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• SciCrunch
• 17 years ago - by Anonymous

Knowledgebase of fusion transcripts collected from various public resources such as the Sanger CGP, OMIM, PubMed, and Mitelman's database. It is an alignment viewer to facilitate examining reliability of fusion transcripts and inferring functional significance., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

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• SciCrunch
• 17 years ago - by Anonymous

A graphical viewer of phylogenetic trees and a program for producing publication-ready figures. It is designed to display summarized and annotated trees produced by BEAST.

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• SciCrunch
• 17 years ago - by Anonymous

Neuroshare aims to develop a standard for accessing neurophysiological data from any vendor's acquisition device or software. An API is defined, and vendors and communities are encouraged to provide implementations of a library of functions that can read data files collected with that vendor's instrument or software. The neuroshare.org website is a collaborative, vendor-neutral area dedicated to public domain standards and software for neurophysiology.This website is part of an SBIR program funded by the National Institute for Neural Disorders and Stroke and it is currently being administered by Bionic Technologies, LLC. The goals of the SBIR program are to (Phase I) create open library and format standards for neurophysiological experiment data and (Phase II) create a set of free, open-source software tools for low-level handling and processing of neurophysiological data. Upon completion of Phase I and II, neuroshare.org will be maintained by a yet to be determined consortium of government, academic and industry partners. The SBIR was awarded in the fall of 2001 and Phase I officially began in Dec, 2001. The detailed goals of the program are summarized below:Phase I goals :(1) Establish a working group to develop and define the API library of functions.(2) A vendor-neutral web site to facilitate the development of the standards and software and publish the completed products. This site has been dubbed Neuroshare. The home page can be found at neuroshare.sourceforge.net.(3) An open, standardized API library definition for accessing neurophysiology data files. This will allow developers to produce analysis programs that can access a variety of proprietary data formats through libraries supplied by the data format owners. The manner of support will be completely determined by the research groups and vendors that supply the libraries. The Phase I standard was created by a working group consisting of international members from industry and academia. Draft standards were published for public review and comment on the neuroshare web site and revised by the working group.The grant has been awarded as a fast-track program so that Phase II begins immediately upon completion of the Phase I milestones in June 2002. Phase II will produce :(1) A set of neuroshare-compliant API libraries for existing data formats developed in collaboration with individual equipment vendors and research groups.(2) A utility for analyzing compliant API libraries for integrity and specification conformance, as well as for error checking imported data files.(3) A set of template programs in C that are meant to be used as an example on how to create a Neuroshare API compliant library and how to call it from an application,(4) An open, standardized file format for neurophysiological experiment data. This format will provide research groups and vendors with a file format for exchanging and/or publishing neural data. The format will also be powerful enough for use as a native format for researchers or vendors that wish to support it in data acquisition hardware/software.(5) Import filters that interface neuroshare-compliant API libraries to Visual Basic, MATLAB, and LabVIEW, NeuroExplorer, and Stranger analysis environments.(6) A utility program for quick header information viewing and searching to aid the organization and management of data files in the standard and proprietary formats.(7) A data file editing program for reviewing, editing, annotating, and splicing neural data files through the neuroshare API libraries and/or standard file formats. The suite will be developed in C, optimized for speed, and will run within 32-bit Windows operating systems. The availability of source code will enable eventual ports to Unix/Linux if desired(8) An add-on for the editing program that will allow review and real-time playback of multi-modal data accessible through the API and/or standard file format. These modes will include neurophysiological signals such as spikes, local field potentials and EEG, as well as experimental signals such as kinematics, stimulation, audio, video, and imaging data.(9) C and MATLAB framework programs for detection and classification of extracellular spikes in the standard data files based on classical and user-supplied algorithms.(10) A complete MATLAB application for reading data from the standard format and performing reverse correlation analysis. This program will serve as a tutorial and modifiable template for users performing analysis in MATLAB.(11) A set of export filters for creating neurophysiological data files with the neural simulation environments NEURON, NEOSIM, GENESIS, and NSL.(12) A comprehensive documentation, and help file set for all of the developed applications.Phase II will require two years of development work and software products will be made available as they are completed. As stated above, the Phase II software products will be made available as free, open-source tools. We have not decided on a license model yet, but are currently leaning towards the GNU General Public License. Revisions and bug-fixes will be maintained through the neuroshare.org website. The mission of neuroshare.org is very focused, but the specific goal list of Phase II may evolve somewhat as software is released and user feedback is received. We very interested in public suggestions about how to improve this development effort and web site. Please direct your feedback to commentsneuroshare.org or refer to our contacts page for other addresses.BackgroundThis endeavor grew out of a meeting held at the Society for Neuroscience 2000 Annual Conference in New Orleans (agenda posted here) to discuss the development of standard data formats for neuroscience. From this meeting, it was clear that although everyone supported the idea of better data portability, many vendors present wanted a standardized API (Application Program Interface) library rather than a universal data format. Based on this meeting, we submitted an SBIR application (with letters of support from key attendants of the SFN meeting) to fund the development of a standardized API definition, data format, and a suite of open source data handling and review tools.

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• SciCrunch
• 17 years ago - by Anonymous

hiPathDB is an integrated pathway database that combines the curated human pathway data of NCI-Nature PID, Reactome, BioCarta and KEGG. In total, it includes 1661 pathways consisting of 8976 distinct physical entities. (2010.03.09) hiPathDB provides two different types of integration. The pathway-level integration, conceptually a simple collection of individual pathways, was achieved by devising an elaborate model that takes distinct features of four databases into account and subsequently reformatting all pathways in accordance with our model. The entity-level integration creates a single unified pathway that encompasses all pathways by merging common components. Even though the detailed molecular-level information such as complex formation or post-translational modifications tends to be lost, such integration makes it possible to investigate signaling network over the entire pathways and allows identification of pathway cross-talks. Another strong merit of hiPathDB is the built-in pathway visualization module that supports explorative studies of complex networks in an interactive fashion. The layout algorithm is optimized for virtually automatic visualization of the pathways.

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• SciCrunch
• 15 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software Python package that provides infrastructure to process data from high-throughput sequencing assays. While the main purpose of HTSeq is to allow you to write your own analysis scripts, customized to your needs, there are also a couple of stand-alone scripts for common tasks that can be used without any Python knowledge.

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• SciCrunch
• 13 years ago - by Anonymous

CISCRP is a resource for information on participation in, understanding of, and resources for clinical research participants and scientists. The mission of the Center is to educate, inform and empower patients, the public, medical and research professionals, the media and policymakers about clinical research participation and what it means to be an active participant in the clinical research process, promote greater awareness and understanding of clinical research participation and the role that it plays in public health, facilitate more effective collaboration among all members of the clinical research enterprise, and provide resources for the research community to better understand the study volunteer. To that end, the Center has developed a broad national awareness and education initiative in order to better inform the public at large about clinical study information. Furthermore, on its website, the Center offers program and event information related to clinical trials, an information center with facts, figures, informational resources, and FAQs for both patients and researchers, and a mailing list of clinical trial information. :The Center also maintains its own search engine website, : :searchclinicaltrials.org : : :, for those looking for further clinical trial information. The Center for Information and Study on Clinical Research Participation is located in Dedham, MA. :NIF thanks the : :Parkinson's Disease Foundation : : :for their referral of this resource to us.

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• SciCrunch
• 17 years ago - by Anonymous

The Cardiovascular Proteomics Center is a research center funded by the NIH/NHLBI to analyze and identify proteins that may be modified or created by oxidative stress. The CPC is developing and applying new proteomics methodology and instrumentation to the analysis of known proteins and those yet to be discovered.

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• SciCrunch
• 15 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Algorithm for high-dimensional biomarker discovery and explanation that identifies genes, pathways, or taxa characterizing the differences between two or more biological conditions. The algorithm identifies features that are statistically different among biological classes, then performs additional tests to assess whether these differences are consistent with respect to expected biological behavior. Statistical significance and biological relevance are emphasized., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

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• SciCrunch
• 11 years ago - submitted by Kristen Jensen

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 26, 2016. The NeuroFed resource is a listing of neuroscience research funding contacts in the Federal government. It is an informal compendium (PDF) of names and contact information for nearly 300 research grant and scientific review administrators in 21 organizational units of the federal government. An electronic (PDF) version of the most recent update of this list is available on the Society for Neuroscience website at: http://www.sfn.org/index.aspx?pagename=professionalDevelopment_training. The list is updated annually by NIH personnel.

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• SciCrunch
• 17 years ago - by Anonymous