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http://www.neuroconstruct.org/

Software for simulating complex networks of biologically realistic neurons, i.e. models incorporating dendritic morphologies and realistic cell membrane conductance, implemented in Java and generates script files for the NEURON and GENESIS simulators, with support for other simulation platforms (including PSICS and PyNN) in development. neuroConstruct is being developed in the Silver Lab in the Department of Neuroscience, Physiology and Pharmacology at UCL and uses the latest NeuroML specifications, including MorphML, ChannelML and NetworkML. Some of the key features of neuroConstruct are: Creation of networks of biologically realistic neurons, positioned in 3D space. Complex connectivity patterns between cell groups can be specified for the networks. Can import morphology files in GENESIS, NEURON, Neurolucida, SWC and MorphML format for inclusion in network models. Simulations can be run on the NEURON or GENESIS platforms. Cellular processes (synapses/channel mechanisms) can be imported from native script files or created in ChannelML. Recording of simulation data generated by the simulation and visualization/analysis of data. Stored simulation runs can be viewed and managed through the Simulation Browser interface.

Proper citation: neuroConstruct (RRID:SCR_007197) Copy   

•   Source: SciCrunch Registry

http://t1dbase.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 26,2019. In October 2016, T1DBase has merged with its sister site ImmunoBase (https://immunobase.org). Documented on March 2020, ImmunoBase ownership has been transferred to Open Targets (https://www.opentargets.org). Results for all studies can be explored using Open Targets Genetics (https://genetics.opentargets.org). Database focused on genetics and genomics of type 1 diabetes susceptibility providing a curated and integrated set of datasets and tools, across multiple species, to support and promote research in this area. The current data scope includes annotated genomic sequences for suspected T1D susceptibility regions; genetic data; microarray data; and global datasets, generally from the literature, that are useful for genetics and systems biology studies. The site also includes software tools for analyzing the data.

Proper citation: T1DBase (RRID:SCR_007959) Copy   

•   Source: SciCrunch Registry

http://rfam.xfam.org/

The Rfam database is a collection of RNA families, each represented by multiple sequence alignments, consensus secondary structures and covariance models (CMs). The families in Rfam break down into three broad functional classes: Non-coding RNA genes, structured cis-regulatory elements and self-splicing RNAs. Typically these functional RNAs often have a conserved secondary structure which may be better preserved than the RNA sequence. The CMs used to describe each family are a slightly more complicated relative of the profile hidden Markov models (HMMs) used by Pfam. CMs can simultaneously model RNA sequence and the structure in an elegant and accurate fashion. Rfam is also available via FTP. You can find data in Rfam in various ways... * Analyze your RNA sequence for Rfam matches * View Rfam family annotation and alignments * View Rfam clan details * Query Rfam by keywords * Fetch families or sequences by NCBI taxonomy * Enter any type of accession or ID to jump to the page for a Rfam family, sequence or genome

Proper citation: Rfam (RRID:SCR_007891) 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://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

https://vertebrate.genenames.org/

Software resource for vertebrate gene nomenclature. Database of gene symbols. Coordinates with vertebrate nomenclature committees, MGNC (mouse), RGNC (rat), CGNC (chicken), AGNC (Anole green lizard), XNC (Xenopus frog) and ZNC (zebrafish), to ensure genes are named in line with their human homologs.

Proper citation: VGNC (RRID:SCR_017514) Copy   

•   Source: SciCrunch Registry

http://www.roslin.ed.ac.uk/about-roslin/

The world''s largest collection of tick cell lines, enabling scientists to carry out advanced research. This biobank is establishing a collection of all the continuous cell lines derived from ixodid and argasid ticks of medical and veterinary importance available worldwide now and in future. Ticks are blood feeding arthropods which transmit many human and animal diseases. Research into prevention and cure of these diseases, which are caused by viruses, bacteria and protozoa, is greatly assisted by the use of cell culture systems which enable study of both how tick cells function, and how and why ticks transmit these disease-causing pathogens. Cell lines will always be shipped to recipient laboratories as growing cultures, since we cannot guarantee successful resuscitation of frozen stabilates. Tick cells in culture can tolerate the range of temperatures experienced during transit by air for up to a week. Training: We will provide training in tick cell line care and maintenance. This is an essential component of successful transfer of tick cells to, and their establishment in, laboratories with little or no previous experience of tick cell culture. Recipient scientists (preferably the person who will actually look after the cells) can visit the biobank for between 2 days and 2 weeks, depending on their level of previous experience, to be trained in the specific approach and methods for tick cell cultivation. Establishment of new cell lines: In response to requests and on receipt of suitable starting material (engorged female or moulting nymphal ticks), we will attempt to establish new cell lines from tick species or strains which are not already represented in the collection. Deposition of new tick cell lines: We invite researchers anywhere in the world who have established new tick cell lines to deposit samples for safekeeping free of charge and, if requested, for distribution alongside the existing biobank portfolio.

Proper citation: Roslin Wellcome Trust Tick Cell Biobank (RRID:SCR_004228) Copy   

•   Source: SciCrunch Registry

http://www.sharmuk.org/

A not for profit organization to accelerate research into aging by sharing resources: providing access to cost and time effective, aged murine tissue through a biorepository and database of live ageing colonies, as well as promoting the networking of researchers and dissemination of knowledge through its online collaborative environment; MiCEPACE. ShARM will provide valuable resources for the scientific community while helping to reduce the number of animals used in vital research into aging. The biobank of tissue and networking facility will enable scientists to access shared research material and data. By making use of collective resources, the number of individual animals required in research experiments can be minimized. The project also has the added value of helping to reduce the costs of research by connecting scientists, pooling resource and combining knowledge. ShARM works in partnership with MRC Harwell and the Centre for Intergrated Research into Musculoskeletal Ageing (CIMA).

Proper citation: ShARM (RRID:SCR_003120) Copy   

•   Source: SciCrunch Registry

http://tiger.bsc.es

Resource enables integrative exploration of genetic and epigenetic basis of development of Type 2 Diabetes, together with other associated functional, molecular and clinical data, centered in biology and role of pancreatic beta cells.The gene expression regulatory variation landscape of human pancreatic islets.

Proper citation: TIGER Data Portal (RRID:SCR_023626) Copy   

•   Source: SciCrunch Registry

https://github.com/mskcc/lohhla

Software tool to evaluate HLA loss using next-generation sequencing data. Computational tool to determine HLA allele-specific copy number from sequencing data.

Proper citation: LOHHLA (RRID:SCR_023690) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/science/tools/alien-hunter

Software for the prediction of putative Horizontal Gene Transfer (HGT) events with the implementation of Interpolated Variable Order Motifs (IVOMs). The predictions (embl format) can be automatically loaded into Artemis genome viewer.

Proper citation: Alien-hunter (RRID:SCR_015967) Copy   

•   Source: SciCrunch Registry

https://www.flimfit.org/

Software package for quantitative analysis of large Fluorescence Lifetime Imaging Microscopy (FLIM) data, including global analysis. It is able to routinely analyse multi-well plate FLIM datasets on conventional PC workstations in a reasonable time., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: FLIMfit (RRID:SCR_016298) Copy   

•   Source: SciCrunch Registry

https://www.sanger.ac.uk/science/tools/reapr

Software tool to identify errors in genome assemblies without need for reference sequence. Can be used in any stage of assembly pipeline to automatically break incorrect scaffolds and flag other errors in assembly for manual inspection. Reports mis-assemblies and other warnings, and produces new broken assembly based on error calls.

Proper citation: Recognition of Errors in Assemblies using Paired Reads (RRID:SCR_017625) Copy   

•   Source: SciCrunch Registry

http://hmri.info

Software toolbox for quantitative MRI in neuroscience and clinical research. Open source and flexible tool for qMRI data handling and processing. Allows estimation of high quality multi parameter qMRI maps followed by spatial registration in common space for statistical analysis.

Proper citation: hMRI-toolbox (RRID:SCR_017682) Copy   

•   Source: SciCrunch Registry

https://www2.mrc-lmb.cam.ac.uk/groups/murshudov/content/balbes/balbes_layout.html

Software system for solving protein structures using x-ray crystallographic data. Automatic molecular replacement pipeline for molecular replacement in CCP4. Integrates into one system all components necessary for solving crystal structure by Molecular Replacement. System is automated so that it needs no user intervention when running combination of jobs such as model searching, molecular replacement and refinement.

Proper citation: BALBES (RRID:SCR_018763) Copy   

•   Source: SciCrunch Registry

http://www.opensourcebrain.org

A resource for sharing and collaboratively developing computational models of neural systems. While models can be submitted and developed in any format, the use of open standards such as NeuroML and PyNN is encouraged, to ensure transparency, modularity, accessibility and cross simulator portability. OSB will provide advanced facilities to analyze, visualize and transform models in these formats, and to connect researchers interested in models of specific neurons, brain regions and disease states. Research themes include: Basal ganglia modelling, Cerebellar Granule cell modelling, Cerebellar modelling, Hippocampal modelling, Neocortical modelling, Whole brain models. Additional themes are welcome.

Proper citation: Open Source Brain (RRID:SCR_001393) Copy   

•   Source: SciCrunch Registry

http://shiny.chemgrid.org/boxplotr/

Web tool written in R for generation of box plots with R packages shiny, beanplot4, vioplot, beeswarm and RColorBrewer, and hosted on shiny server to allow for interactive data analysis. Data are held temporarily and discarded as soon as session terminates.Represents both summary statistics and distribution of primary data. Enables visualization of minimum, lower quartile, median, upper quartile and maximum of any data set.Data matrix can be uploaded as file or pasted into application. May be downloaded to run locally or as virtual machine for VMware and VirtualBox.

Proper citation: BoxPlotR (RRID:SCR_015629) Copy   

•   Source: SciCrunch Registry

https://github.com/sanger-pathogens/Bio-Tradis

Analysis software for the output from TraDIS (Transposon Directed Insertion Sequencing) analyses of dense transposon mutant libraries. The Bio-Tradis analysis pipeline is implemented as an extensible Perl library which can either be used as is, or as a basis for the development of more advanced analysis tools.

Proper citation: Bio-tradis (RRID:SCR_015993) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/release/bioc/html/SC3.html

Software tool for the unsupervised clustering of cells from single cell RNA-Seq experiments. SC3 is capable of identifying subclones from the transcriptomes of neoplastic cells collected from patients.

Proper citation: SC3 (RRID:SCR_015953) Copy   

•   Source: SciCrunch Registry

https://github.com/neurodroid/stimfit

Software for viewing and analyzing electrophysiological data. It features an embedded Python shell that allows you to extend the program functionality by using numerical libraries such as NumPy and SciPy.

Proper citation: Stimfit (RRID:SCR_016050) Copy   

•   Source: SciCrunch Registry