<tools xmlns="biotoolsSchema" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="biotoolsSchema file:///E:/repos/GitHub/biotoolsShim/genericxml2xml/versions/biotools-3.3.0/biotools_3.3.0.xsd"><tool><name>SIGNAL</name><description>SIGNAL (Selection by Iterative pathway Group and Network Analysis Looping) is a web-based iterative analysis platform integrating pathway and network approaches optimizes hit selection from genome-scale assays.</description><homepage>https://signal.niaid.nih.gov</homepage><biotoolsID>signal</biotoolsID><biotoolsCURIE>biotools:signal</biotoolsCURIE><toolType>Web application</toolType><topic><uri>http://edamontology.org/topic_0602</uri><term>Molecular interactions, pathways and networks</term></topic><topic><uri>http://edamontology.org/topic_0091</uri><term>Bioinformatics</term></topic><topic><uri>http://edamontology.org/topic_2229</uri><term>Cell biology</term></topic><language>R</language><function><operation><uri>http://edamontology.org/operation_3928</uri><term>Pathway analysis</term></operation><operation><uri>http://edamontology.org/operation_3927</uri><term>Network analysis</term></operation></function><publication><doi>10.1016/j.cels.2021.03.001</doi><pmid>33894945</pmid><pmcid>PMC7613048</pmcid><type>Primary</type></publication><credit><name>Iain D.C. Fraser</name><email>fraseri@nih.gov</email><typeEntity>Person</typeEntity><typeRole>Primary contact</typeRole></credit></tool><tool><name>SignalP</name><description>Prediction of the presence and location of signal peptide cleavage sites in amino acid sequences from different organisms.</description><homepage>http://cbs.dtu.dk/services/SignalP/</homepage><biotoolsID>signalp</biotoolsID><biotoolsCURIE>biotools:signalp</biotoolsCURIE><version>4.1</version><otherID><value>rrid:SCR_015644</value><type>rrid</type></otherID><toolType>Command-line tool</toolType><toolType>Web application</toolType><topic><uri>http://edamontology.org/topic_3510</uri><term>Protein sites, features and motifs</term></topic><operatingSystem>Linux</operatingSystem><operatingSystem>Mac</operatingSystem><license>Other</license><collectionID>CBS</collectionID><maturity>Mature</maturity><cost>Free of charge (with restrictions)</cost><function><operation><uri>http://edamontology.org/operation_0418</uri><term>Protein signal peptide detection</term></operation><operation><uri>http://edamontology.org/operation_0422</uri><term>Protein cleavage site prediction</term></operation><input><data><uri>http://edamontology.org/data_2044</uri><term>Sequence</term></data><format><uri>http://edamontology.org/format_1929</uri><term>FASTA</term></format></input><output><data><uri>http://edamontology.org/data_1277</uri><term>Protein features</term></data><format><uri>http://edamontology.org/format_2305</uri><term>GFF</term></format></output><output><data><uri>http://edamontology.org/data_2955</uri><term>Sequence report</term></data></output><note>predicts the presence and location of signal peptide cleavage sites in amino acid sequences from different organisms</note></function><link><url>http://www.cbs.dtu.dk/cgi-bin/sw_request?signalp</url><type>Repository</type></link><download><url>http://www.cbs.dtu.dk/cgi-bin/sw_request?signalp</url><type>Source code</type></download><download><url>http://www.cbs.dtu.dk/cgi-bin/sw_request?signalp</url><type>Binaries</type></download><documentation><url>http://www.cbs.dtu.dk/services/SignalP</url><type>General</type></documentation><publication><doi>10.1038/nmeth.1701</doi><pmid>21959131</pmid><type>Primary</type></publication><credit><name>TN Petersen</name><typeEntity>Person</typeEntity><typeRole>Developer</typeRole></credit><credit><name>CBS</name><typeEntity>Institute</typeEntity><typeRole>Provider</typeRole></credit><credit><name>Henrik Nielsen</name><email>hnielsen@cbs.dtu.dk</email><orcidid>http://orcid.org/0000-0002-9412-9643</orcidid><typeRole>Developer</typeRole></credit><credit><name>Henrik Nielsen</name><email>hnielsen@cbs.dtu.dk</email><orcidid>http://orcid.org/0000-0002-9412-9643</orcidid><typeEntity>Person</typeEntity><typeRole>Primary contact</typeRole></credit></tool><tool><name>SignacX</name><description>Cell type classification and discovery across diseases, technologies and tissues reveals conserved gene signatures and enables standardized single-cell readouts.

Get the most out of your single cell data.

SignacX is software developed and maintained by the Savova lab at Sanofi with a focus on single cell genomics for clinical applications. SignacX classifies the cellular phenotype for each individual cell in single cell RNA-sequencing data using neural networks trained with sorted bulk gene expression data from the Human Primary Cell Atlas. To learn more, check out the pre-print, website and code base.</description><homepage>https://github.com/mathewchamberlain/SignacX</homepage><biotoolsID>signacx</biotoolsID><biotoolsCURIE>biotools:signacx</biotoolsCURIE><toolType>Desktop application</toolType><topic><uri>http://edamontology.org/topic_0625</uri><term>Genotype and phenotype</term></topic><topic><uri>http://edamontology.org/topic_3474</uri><term>Machine learning</term></topic><topic><uri>http://edamontology.org/topic_0634</uri><term>Pathology</term></topic><topic><uri>http://edamontology.org/topic_2229</uri><term>Cell biology</term></topic><topic><uri>http://edamontology.org/topic_3170</uri><term>RNA-Seq</term></topic><language>R</language><license>GPL-3.0</license><function><operation><uri>http://edamontology.org/operation_0314</uri><term>Gene expression profiling</term></operation><operation><uri>http://edamontology.org/operation_3802</uri><term>Sorting</term></operation><operation><uri>http://edamontology.org/operation_3435</uri><term>Standardisation and normalisation</term></operation></function><publication><doi>10.1101/2021.02.01.429207</doi></publication><publication><doi>10.21203/RS.3.RS-199733/V1</doi></publication><credit><name>Virginia Savova</name><email>Virginia.Savova@sanofi.com</email><typeEntity>Person</typeEntity></credit></tool><tool><name>Signac</name><description>Multimodal single-cell chromatin analysis with Signac.

A New Algorithm for Finding Marker Genes in Single-Cell Transcriptomic Data.

Signac - A versatile package for Single-cell RNA-Seq analysis.

We introduce Signac, a versatile R package to facilitate the analysis workflow for single-cell data. It helps to find marker genes faster and more accurate, search for cells with similar expression profiles, integrate multiple datasets in the BioTuring Browser database (know more about BioTuring Browser), etc. For users with a limited computational resource, we provide the helper functions to exercise all analyses for the large-scale datasets from disk. Because of its speed and flexibility, it can be adapted to any existing R analysis pipeline to help explore single-cell data more efficient.

Signac is an extension of Seurat for the analysis of single-cell chromatin data.</description><homepage>https://satijalab.org/signac/</homepage><biotoolsID>signac</biotoolsID><biotoolsCURIE>biotools:signac</biotoolsCURIE><topic><uri>http://edamontology.org/topic_0203</uri><term>Gene expression</term></topic><topic><uri>http://edamontology.org/topic_3170</uri><term>RNA-Seq</term></topic><topic><uri>http://edamontology.org/topic_0625</uri><term>Genotype and phenotype</term></topic><topic><uri>http://edamontology.org/topic_2229</uri><term>Cell biology</term></topic><topic><uri>http://edamontology.org/topic_3512</uri><term>Gene transcripts</term></topic><language>C++</language><language>R</language><language>Python</language><function><operation><uri>http://edamontology.org/operation_3222</uri><term>Peak calling</term></operation><operation><uri>http://edamontology.org/operation_2495</uri><term>Expression analysis</term></operation><operation><uri>http://edamontology.org/operation_3935</uri><term>Dimensionality reduction</term></operation><operation><uri>http://edamontology.org/operation_3196</uri><term>Genotyping</term></operation><operation><uri>http://edamontology.org/operation_3891</uri><term>Essential dynamics</term></operation></function><link><url>https://github.com/bioturing/signac</url><type>Repository</type></link><link><url>https://cloud.r-project.org/package=Signac</url><type>Other</type></link><link><url>https://github.com/timoast/signac</url><type>Repository</type></link><link><url>https://github.com/timoast/signac-paper</url><type>Repository</type></link><publication><doi>10.1101/2020.11.09.373613</doi></publication><publication><doi>10.1101/2020.11.16.384479</doi></publication><credit><name>Tim Stuart</name><email>tstuart@nygenome.org</email><typeEntity>Person</typeEntity></credit><credit><name>Rahul Satija</name><email>rsatija@nygenome.org</email><typeEntity>Person</typeEntity></credit><credit><name>Son Pham</name><email>sonpham@bioturing.com</email><typeEntity>Person</typeEntity></credit></tool><tool><name>eSIGNAL</name><description>eSignal is a database of eMOTIFs and eMATRICES generated exclusively from signal transduction proteins. ESIGNAL can be used to discover signal transduction functions in new proteins.</description><homepage>http://motif.stanford.edu/distributions/esignal/</homepage><biotoolsID>esignal</biotoolsID><biotoolsCURIE>biotools:esignal</biotoolsCURIE><version>1.0</version><toolType>Command-line tool</toolType><topic><uri>http://edamontology.org/topic_0078</uri><term>Proteins</term></topic><operatingSystem>Linux</operatingSystem><language>C++</language><language>Perl</language><language>C</language><function><operation><uri>http://edamontology.org/operation_2479</uri><term>Protein sequence analysis</term></operation></function><link><url>http://www.mybiosoftware.com/esignal-1-0-database-medline-mesh-terms-protein-motifs-detect-signal-transduction-proteins.html</url><type>Software catalogue</type></link><documentation><url>http://motif.stanford.edu/distributions/esignal/</url><type>User manual</type></documentation><credit><url>http://motif.stanford.edu/</url><typeEntity>Person</typeEntity><typeRole>Primary contact</typeRole></credit></tool></tools>