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http://mistdb.com

Database which contains the signal transduction proteins for complete and draft bacterial and archaeal genomes. The MiST2 database identifies and catalogs the repertoire of signal transduction proteins in microbial genomes.

Proper citation: MiST - Microbial Signal Transduction database (RRID:SCR_003166) Copy   

•   Source: SciCrunch Registry

http://zebrafinch.brainarchitecture.org/

Atlas of high resolution Nissl stained digital images of the brain of the zebra finch, the mainstay of songbird research. The cytoarchitectural high resolution photographs and atlas presented here aim at facilitating electrode placement, connectional studies, and cytoarchitectonic analysis. This initial atlas is not in stereotaxic coordinate space. It is intended to complement the stereotaxic atlases of Akutegawa and Konishi, and that of Nixdorf and Bischof. (Akutagawa E. and Konishi M., stereotaxic atalas of the brain of zebra finch, unpublished. and Nixdorf-Bergweiler B. E. and Bischof H. J., A Stereotaxic Atlas of the Brain Of the Zebra Finch, Taeniopygia Guttata, http://www.ncbi.nlm.nih.gov.) The zebra finch has proven to be the most widely used model organism for the study of the neurological and behavioral development of birdsong. A unique strength of this research area is its integrative nature, encompassing field studies and ethologically grounded behavioral biology, as well as neurophysiological and molecular levels of analysis. The availability of dimensionally accurate and detailed atlases and photographs of the brain of male and female animals, as well as of the brain during development, can be expected to play an important role in this research program. Traditionally, atlases for the zebra finch brain have only been available in printed format, with the limitation of low image resolution of the cell stained sections. The advantages of a digital atlas over a traditional paper-based atlas are three-fold. * The digital atlas can be viewed at multiple resolutions. At low magnification, it provides an overview of brain sections and regions, while at higher magnification, it shows exquisite details of the cytoarchitectural structure. * It allows digital re-slicing of the brain. The original photographs of brain were taken in certain selected planes of section. However, the brains are seldom sliced in exactly the same plane in real experiments. Re-slicing provides a useful atlas in user-chosen planes, which are otherwise unavailable in the paper-based version. * It can be made available on the internet. High resolution histological datasets can be independently evaluated in light of new experimental anatomical, physiological and molecular studies.

Proper citation: Zebrafinch Brain Architecture Project (RRID:SCR_004277) Copy   

•   Source: SciCrunch Registry

http://avis.princeton.edu/pixie/index.php

bioPIXIE is a general system for discovery of biological networks through integration of diverse genome-wide functional data. This novel system for biological data integration and visualization, allows you to discover interaction networks and pathways in which your gene(s) (e.g. BNI1, YFL039C) of interest participate. The system is based on a Bayesian algorithm for identification of biological networks based on integrated diverse genomic data. To start using bioPIXIE, enter your genes of interest into the search box. You can use ORF names or aliases. If you enter multiple genes, they can be separated by commas or returns. Press ''submit''. bioPIXIE uses a probabilistic Bayesian algorithm to identify genes that are most likely to be in the same pathway/functional neighborhood as your genes of interest. It then displays biological network for the resulting genes as a graph. The nodes in the graph are genes (clicking on each node will bring up SGD page for that gene) and edges are interactions (clicking on each edge will show evidence used to predict this interaction). Most likely, the first results to load on the results page will be a list of significant Gene Ontology terms. This list is calculated for the genes in the biological network created by the bioPIXIE algorithm. If a gene ontology term appears on this list with a low p-value, it is statistically significantly overrepresented in this biological network. As you move the mouse over genes in the network, interactions involving these genes are highlighted. If you click on any of the highlighted interactions graph, evidence pop-up window will appear. The Evidence pop-up lists all evidence for this interaction, with links to the papers that produced this evidence - clicking these links will bring up the relevant source citation(s) in PubMed. You may need to download the Adobe Scalable Vector Graphic (SVG) plugin to utilize the visualization tool (you will be prompted if you need it).

Proper citation: bioPIXIE (RRID:SCR_004182) Copy   

•   Source: SciCrunch Registry

http://www.lipidmaps.org/data/structure/

Collection of structures and annotations of biologically relevant lipids that contains unique lipid structures. Structures of lipids from : LIPID MAPS Consortium's core laboratories and partners; lipids identified by LIPID MAPS experiments; biologically relevant lipids manually curated from LIPID BANK, LIPIDAT, Lipid Library, Cyberlipids, ChEBI and other public sources; novel lipids submitted to peer-reviewed journals; and computationally generated structures for appropriate classes. All the lipid structures adhere to the structure drawing rules proposed by the LIPID MAPS consortium. A number of structure viewing options are offered: gif image (default), Chemdraw (requires Chemdraw ActiveX/Plugin), MarvinView (Java applet) and JMol (Java applet). All lipids have been classified using the LIPID MAPS Lipid Classification System. Each lipid structure has been assigned a LIPID MAPS ID (LM_ID) which reflects its position in the classification hierarchy. In addition to a classification-based retrieval of lipids, users can search using either text-based or structure-based search options.

Proper citation: LIPID MAPS Structure Database (RRID:SCR_003817) Copy   

•   Source: SciCrunch Registry

http://integromedb.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 26, 2016. Search engine that integrates over 100 curated and publicly contributed data sources and provides integrated views on the genomic, proteomic, transcriptomic, genetic and functional information currently available. Information featured in the database includes gene function, orthologies, gene expression, pathways and protein-protein interactions, mutations and SNPs, disease relationships, related drugs and compounds.

Proper citation: IntegromeDB (RRID:SCR_004620) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/thornton-srv/databases/profunc/index.html

The ProFunc server had been developed to help identify the likely biochemical function of a protein from its three-dimensional structure. It uses both sequence- and structure-based methods including fold matching, residue conservation, surface cleft analysis, and functional 3D templates, to identify both the protein''''s likely active site and possible homologues in the PDB. Often, where one method fails to provide any functional insight another may be more helpful. You can submit your own structure, analyze an existing PDB entry, or retrieve the results of a previously submitted run. The files are usually stored for about 6 months before being deleted. However, they are stored on a partition that is not backed up; so, in principle, they could disappear at any time.

Proper citation: ProFunc (RRID:SCR_004450) Copy   

•   Source: SciCrunch Registry

http://www.phenologs.org/

Database for identifying orthologous phenotypes (phenologs). Mapping between genotype and phenotype is often non-obvious, complicating prediction of genes underlying specific phenotypes. This problem can be addressed through comparative analyses of phenotypes. We define phenologs based upon overlapping sets of orthologous genes associated with each phenotype. Comparisons of >189,000 human, mouse, yeast, and worm gene-phenotype associations reveal many significant phenologs, including novel non-obvious human disease models. For example, phenologs suggest a yeast model for mammalian angiogenesis defects and an invertebrate model for vertebrate neural tube birth defects. Phenologs thus create a rich framework for comparing mutational phenotypes, identify adaptive reuse of gene systems, and suggest new disease genes. To search for phenologs, go to the basic search page and enter a list of genes in the box provided, using Entrez gene identifiers for mouse/human genes, locus ids for yeast (e.g., YHR200W), or sequence names for worm (e.g., B0205.3). It is expected that this list of genes will all be associated with a particular system, trait, mutational phenotype, or disease. The search will return all identified model organism/human mutational phenotypes that show any overlap with the input set of the genes, ranked according to their hypergeometric probability scores. Clicking on a particular phenolog will result in a list of genes associated with the phenotype, from which potential new candidate genes can identified. Currently known phenotypes in the database are available from the link labeled ''Find phenotypes'', where the associated gene can be submitted as queries, or alternately, can be searched directly from the link provided.

Proper citation: Phenologs (RRID:SCR_005529) Copy   

•   Source: SciCrunch Registry

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

Facility houses imaging technologies ranging from super resolution (~ 0.120 um to 0.020 um) to microscopic (~ 0.300 um) to mesoscopic (~ 1 um) biomedical imaging. Imaging specialists provide training and/or actively assist researchers collecting images across imaging instrumentation. Instrumentation includes Zeiss ELYRA PS.1 is inverted microscope for super resolution (SR) structured illumination microscopy (SIM) and single molecule localization microscopy (SMLM) including, PhotoActivated Localization Microscopy (PALM) using photo switchable/convertible fluorescent proteins, Total Internal Reflection Fluorescence (TIRF) and STochastic Optical Reconstruction Microscopy (STORM);Zeiss 800 CLSM with Airyscan is an inverted microscope dramatically increasing conventional confocal image resolution to ~180 nm using Airyscan technology; Zeiss 710 LSM is inverted microscope supporting most basic imaging applications, multi channel and spectral, co localization, live cell, 3D, and time series imaging; Zeiss Celldiscoverer 7 is widefield imaging system for automated, time lapse imaging of live samples; Zeiss Axioscan 7 is high performance whole slide scanning system for fluorescence, brightfield, and polarization imaging;Miltenyi Biotec Ultramicroscope II Light Sheet fluorescence microscope (LSFM) extends fluorescent imaging into true 3D, large scale volumetric imaging of intact tissues, organs, and small organisms. AMCF also houses several high-end data analysis workstations with premier image analysis software including HALO (Indica Labs) and IMARIS (Oxford Instruments) facilitating data rendering, analyses, and presentation options.

Proper citation: University of Nebraska Medical Center Advanced Microscopy Core Facility (RRID:SCR_022467) Copy   

•   Source: SciCrunch Registry

https://github.com/compbiolabucf/PTNet

Graph based learning model for protein expression estimation by considering miRNA-mRNA interactions. Estimates protein levels by considering miRNA-mRNA interaction network, mRNA expression and miRNA expression.

Proper citation: PTNet (RRID:SCR_022975) Copy   

•   Source: SciCrunch Registry

https://github.com/protofilamentdude/Protofilament-Bending-Models

Code is written to be run with Matlab version r2020b or higher. Model accepts wave assay pulse amplitude data, and simultaneously solves and fits protofilament deflection models to deduce fundamental biophysical properties of microtubule protofilaments.

Proper citation: Protofilament Bending Models (RRID:SCR_023062) Copy   

•   Source: SciCrunch Registry

https://github.com/caraweisman/abSENSE

Software to interpret undetected homolog.Method that calculates probability that homolog of given gene would fail to be detected by homology search in given species, even if homolog were present and evolving normally.

Proper citation: abSENSE (RRID:SCR_023223) Copy   

•   Source: SciCrunch Registry

https://med.unr.edu/research/core-facilities-centers/high-spatial-temporal-resolution-imaging-core

Core provides high spatial and temporal resolution imaging methodologies and instrumentation for studying cellular structure, signaling pathways, and function in health and disease. Offers education, training and expertise in advising investigators in the use of the new technologies.

Proper citation: University of Nevada Reno School of Medicine High Spatial and Temporal Resolution Imaging Core Facility (RRID:SCR_024793) Copy   

•   Source: SciCrunch Registry

https://github.com/bioinform/somaticseq

Software accurate somatic mutation detection pipeline implementing stochastic boosting algorithm to produce somatic mutation calls for both single nucleotide variants and small insertions and deletions. NGS variant calling and classification.

Proper citation: SomaticSeq (RRID:SCR_024891) Copy   

•   Source: SciCrunch Registry

https://pephub.databio.org

Web biological metadata server to view, store, and share your sample metadata in form of Portable Encapsulated Projects. PEPhub takes advantage of PEP biological metadata standard to store, edit, and access your PEPs in one place. Components include database where PEPs are stored; API to programmatically read and write PEPs in database; web based user interface to view and manage these PEPs via front end.

Proper citation: PEPhub (RRID:SCR_024892) Copy   

•   Source: SciCrunch Registry

http://plaac.wi.mit.edu/

Web and command-line application to identify proteins with prion-like amino acid composition. Searches protein sequences to identify probable prion subsequences using hidden-Markov model algorithm.

Proper citation: PLAAC (RRID:SCR_024973) Copy   

•   Source: SciCrunch Registry

https://github.com/xinhe-lab/GSFA

Software R package that performs sparse factor analysis and differential gene expression discovery simultaneously on single cell CRISPR screening data.

Proper citation: Guided Sparse Factor Analysis (RRID:SCR_025023) Copy   

•   Source: SciCrunch Registry

https://pycontact.github.io/

Software tool for analysis of non-covalent interactions in molecular dynamics trajectories. Implemented in Python and is universally applicable to any kind of MD trajectory supported by MDAnalysis package.

Proper citation: PyContact (RRID:SCR_025066) Copy   

•   Source: SciCrunch Registry

https://www.npatlas.org

Open access knowledge base for microbial natural products discovery. Database of microbially derived natural product structures. Provides coverage of bacterial and fungal natural products to visualize chemical diversity. Includes compounds and contains referenced data for structure, compound names, source organisms, isolation references, total syntheses, and instances of structural reassignment. Interactive web portal permits searching by structure, substructure, and physical properties. Provides mechanisms for visualizing natural products chemical space and dashboards for displaying author and discovery timeline data. Atlas has been developed under FAIR principles.

Proper citation: Natural Products Atlas (RRID:SCR_025107) Copy   

•   Source: SciCrunch Registry

https://compbio.uth.edu/FusionGDB2/

Functional annotation database of human fusion genes.FusionGDB 2.0 has updates of contents such as up-to-date human fusion genes, fusion gene breakage tendency score with FusionAI deep learning model based on 20 kb DNA sequence around BP, investigation of overlapping between fusion breakpoints with human genomic features across cellular role's categories, transcribed chimeric sequence and following open reading frame analysis with coding potential based on deep learning approach with Ribo-seq read features, and rigorous investigation of protein feature retention of individual fusion partner genes in protein level.

Proper citation: FusionGDB2 (RRID:SCR_025299) Copy   

•   Source: SciCrunch Registry

https://polymerscreen.yale.edu

Open access web app that allows users to search for optimal condition for extraction of membrane proteins into membrane active polymers which allows for retention of native membrane environment around target protein.

Proper citation: MAP Database Guide for Membrane Protein Solubilization (RRID:SCR_025656) Copy   

•   Source: SciCrunch Registry