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http://mtshasta.phys.washington.edu/website/SuperSegger.php

Software package as automated MATLAB based trainable image cell segmentation, fluorescence quantification and analysis suite. Used for high throughput time lapse fluorescence microscopy of in vivo bacterial cells. Robust image segmentation, analysis and lineage tracking of bacterial cells.

Proper citation: SuperSegger (RRID:SCR_018532) Copy   

•   Source: SciCrunch Registry

http://virtualplant.bio.nyu.edu/cgi-bin/vpweb/

Software platform to support systems biology research. Integrates genomic data and provides visualization and analysis tools for exploration of genomic data. Provides tools to generate biological hypotheses.

Proper citation: VirtualPlant (RRID:SCR_022576) Copy   

•   Source: SciCrunch Registry

https://www.gaitor.org

Software suite to analyse gait trials collected with Experimental Dynamic Gait Arena for Rodents. Used for rodent gait analysis.

Proper citation: GAITOR Suite (RRID:SCR_023031) Copy   

•   Source: SciCrunch Registry

https://www.planetmicrobe.org/

Web based platform that enables data discovery from curated historical and on going oceanographic sequencing efforts. Enables discovery and integration of oceanographic ‘omics, environmental and physiochemical data layers. Used to centralize and standardize contextual data associated with major marine 'omic datasets. Used for marine microbiology to discover and analyze interconnected 'omics and environmental data.

Proper citation: Planet Microbe (RRID:SCR_024478) Copy   

•   Source: SciCrunch Registry

https://github.com/katiasmirn/PERFect#perfect-permutation-filtering-package-in-r

Software R package as filtering test for microbiome data. Permutation filtering approach to address two unsolved problems in microbiome data processing: (i) define and quantify loss due to filtering by implementing thresholds and (ii) introduce and evaluate a permutation test for filtering loss to provide a measure of excessive filtering.

Proper citation: PERFect (RRID:SCR_024682) Copy   

•   Source: SciCrunch Registry

http://www.agic.umn.edu/

Portal as data resource, map repository, and GIS service provider for federally-funded scientists conducting research in the Arctic and Antarctic. The PGC holds an extensive collection of satellite imagery and aerial photography at varying resolutions.

Proper citation: Polar Geospatial Center (RRID:SCR_000402) Copy   

•   Source: SciCrunch Registry

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3001096/

Software pipeline to identify MITEs as well as other small Class 2 non autonomous Transposable Elements from genomic DNA data sets. Used for discovering miniature inverted repeat transposable elements from genomic sequences. Can search large genomic data sets including whole genome sequences.

Proper citation: MITE-Hunter (RRID:SCR_020946) Copy   

•   Source: SciCrunch Registry

http://www.ccb.jhu.edu/software/centrifuge/

Software for rapid and sensitive classification of metagenomic sequences. Used for the classification of DNA sequences from microbial samples and analysis of large metagenomics data sets on conventional desktop computers.

Proper citation: Centrifuge Classifier (RRID:SCR_016665) Copy   

•   Source: SciCrunch Registry

https://github.com/iychoi/libra

Hadoop based tool for massive comparative metagenomics analysis. Compute the similarity between metagenomic samples.

Proper citation: Libra (RRID:SCR_016608) Copy   

•   Source: SciCrunch Registry

http://zhoulab.usc.edu/TopDom/

Software tool to identify Topological Domains, which are basic builiding blocks of genome structure. Detects topological domains in a linear time., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: TopDom (RRID:SCR_016964) Copy   

•   Source: SciCrunch Registry

https://picrust.github.io/picrust/

Software package to predict metagenome functional content from marker gene (e.g., 16S rRNA) surveys and full genomes. Used to predict which gene families are present and then combines gene families to estimate the composite metagenome.

Proper citation: PICRUSt (RRID:SCR_016855) Copy   

•   Source: SciCrunch Registry

https://rockd.org/

Map database allows to record your geological observations and uses your location to provide spatially informed suggestions for nearby geologic units, time intervals, and fossils.

Proper citation: rockd (RRID:SCR_024431) Copy   

•   Source: SciCrunch Registry

http://www.ldeo.columbia.edu/core-repository

Core repository and one of the world's most unique and important collections of scientific samples from the deep sea. Sediment cores from every major ocean and sea are archived at the Core Repository. The collection contains approximately 72,000 meters of core composed of 9,700 piston cores; 7,000 trigger weight cores; and 2,000 other cores such as box, kasten, and large diameter gravity cores. They also hold 4,000 dredge and grab samples, including a large collection of manganese nodules, many of which were recovered by submersibles. Over 100,000 residues are stored and are available for sampling where core material is expended. In addition to physical samples, a database of the Lamont core collection has been maintained for nearly 50 years and contains information on the geographic location of each collection site, core length, mineralogy and paleontology, lithology, and structure, and more recently, the full text of megascopic descriptions. Samples from cores and dredges, as well as descriptions of cores and dredges (including digital images and other cruise information), are provided to scientific investigators upon request. Materials for educational purposes and museum displays may also be made available in limited quantities when requests are adequately justified. Various services and data analyses, including core archiving, carbonate analyses, grain size analyses, and RGB line scan imaging, GRAPE, P-wave velocity and magnetic susceptibility runs, can also be provided at cost. The Repository operates a number of labs and instruments dedicated to making fundamental measurements on material entering the repository including several non-destructive methods. Instruments for conducting and/or assisting with analyses of deep-sea sediments include a GeoTek Multi-Sensor Core Logger, a UIC coulometer, a Micromeritics sedigraph, Vane Shear, X-radiograph, Sonic Sifter, freeze dryer, as well as a variety of microscopes, sieves, and sampling tools. They also make these instruments available to the scientific community for conducting analyses of deep-sea sediments. If you are interested in borrowing any field equipment, please contact the Repository Curator.

Proper citation: Lamont-Doherty Core Repository (RRID:SCR_002216) Copy   

•   Source: SciCrunch Registry

http://lrc.geo.umn.edu/laccore/

Archive of almost 20,000 meters of high quality sediment cores from large and small expeditions to lakes all around the world. LacCore advocates for, coordinates, and facilitates core-based research on Earth's continents through collaborative support for logistics, field and laboratory, and data and sample curation and dissemination. They provide a wide variety of fee-based analytical services, as well as offer training and instrument time to lab visitors. They also develop Standard Operating Procedures (SOPs) for local training and adoption by individuals at other labs.

Proper citation: National Lacustrine Core Facility (RRID:SCR_002215) Copy   

•   Source: SciCrunch Registry

http://www.broad.mit.edu/annotation/fungi/fgi/

Produces and analyzes sequence data from fungal organisms that are important to medicine, agriculture and industry. The FGI is a partnership between the Broad Institute and the wider fungal research community, with the selection of target genomes governed by a steering committee of fungal scientists. Organisms are selected for sequencing as part of a cohesive strategy that considers the value of data from each organism, given their role in basic research, health, agriculture and industry, as well as their value in comparative genomics.

Proper citation: Fungal Genome Initiative (RRID:SCR_003169) Copy   

•   Source: SciCrunch Registry

http://alchemy.sourceforge.net/

ALCHEMY is a genotype calling algorithm for Affymetrix and Illumina products which is not based on clustering methods. Features include explicit handling of reduced heterozygosity due to inbreeding and accurate results with small sample sizes. ALCHEMY is a method for automated calling of diploid genotypes from raw intensity data produced by various high-throughput multiplexed SNP genotyping methods. It has been developed for and tested on Affymetrix GeneChip Arrays, Illumina GoldenGate, and Illumina Infinium based assays. Primary motivations for ALCHEMY''s development was the lack of available genotype calling methods which can perform well in the absence of heterozygous samples (due to panels of inbred lines being genotyped) or provide accurate calls with small sample batches. ALCHEMY differs from other genotype calling methods in that genotype inference is based on a parametric Bayesian model of the raw intensity data rather than a generalized clustering approach and the model incorporates population genetic principles such as Hardy-Weinberg equilibrium adjusted for inbreeding levels. ALCHEMY can simultaneously estimate individual sample inbreeding coefficients from the data and use them to improve statistical inference of diploid genotypes at individual SNPs. The main documentation for ALCHEMY is maintained on the sourceforge-hosted MediaWiki system. Features * Population genetic model based SNP genotype calling * Simultaneous estimation of per-sample inbreeding coefficients, allele frequencies, and genotypes * Bayesian model provides posterior probabilities of genotype correctness as quality measures * Growing number of scripts and supporting programs for validation of genotypes against control data and output reformating needs * Multithreaded program for parallel execution on multi-CPU/core systems * Non-clustering based methods can handle small sample sets for empirical optimization of sample preparation techniques and accurate calling of SNPs missing genotype classes ALCHEMY is written in C and developed on the GNU/Linux platform. It should compile on any current GNU/Linux distribution with the development packages for the GNU Scientific Library (gsl) and other development packages for standard system libraries. It may also compile and run on Mac OS X if gsl is installed.

Proper citation: ALCHEMY (RRID:SCR_005761) Copy   

•   Source: SciCrunch Registry

http://www.sgn.cornell.edu/bulk/input.pl?modeunigene

Allows users to download Unigene or BAC information using a list of identifiers or complete datasets with FTP., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Sol Genomics Network - Bulk download (RRID:SCR_007161) Copy   

•   Source: SciCrunch Registry

http://www.nber.org/papers/h0038

A dataset to advance the study of life-cycle interactions of biomedical and socioeconomic factors in the aging process. The EI project has assembled a variety of large datasets covering the life histories of approximately 39,616 white male volunteers (drawn from a random sample of 331 companies) who served in the Union Army (UA), and of about 6,000 African-American veterans from 51 randomly selected United States Colored Troops companies (USCT). Their military records were linked to pension and medical records that detailed the soldiers������?? health status and socioeconomic and family characteristics. Each soldier was searched for in the US decennial census for the years in which they were most likely to be found alive (1850, 1860, 1880, 1900, 1910). In addition, a sample consisting of 70,000 men examined for service in the Union Army between September 1864 and April 1865 has been assembled and linked only to census records. These records will be useful for life-cycle comparisons of those accepted and rejected for service. Military Data: The military service and wartime medical histories of the UA and USCT men were collected from the Union Army and United States Colored Troops military service records, carded medical records, and other wartime documents. Pension Data: Wherever possible, the UA and USCT samples have been linked to pension records, including surgeon''''s certificates. About 70% of men in the Union Army sample have a pension. These records provide the bulk of the socioeconomic and demographic information on these men from the late 1800s through the early 1900s, including family structure and employment information. In addition, the surgeon''''s certificates provide rich medical histories, with an average of 5 examinations per linked recruit for the UA, and about 2.5 exams per USCT recruit. Census Data: Both early and late-age familial and socioeconomic information is collected from the manuscript schedules of the federal censuses of 1850, 1860, 1870 (incomplete), 1880, 1900, and 1910. Data Availability: All of the datasets (Military Union Army; linked Census; Surgeon''''s Certificates; Examination Records, and supporting ecological and environmental variables) are publicly available from ICPSR. In addition, copies on CD-ROM may be obtained from the CPE, which also maintains an interactive Internet Data Archive and Documentation Library, which can be accessed on the Project Website. * Dates of Study: 1850-1910 * Study Features: Longitudinal, Minority Oversamples * Sample Size: ** Union Army: 35,747 ** Colored Troops: 6,187 ** Examination Sample: 70,800 ICPSR Link: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06836

Proper citation: Early Indicators of Later Work Levels Disease and Death (EI) - Union Army Samples Public Health and Ecological Datasets (RRID:SCR_008921) 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/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