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https://ncma.bigelow.org/

National marine phytoplankton collection, maintaining over 2700 strains from around the world, most are marine phytoplankton but they also have benthic, macrophytic, freshwater and heterotrophic organisms - now incorporating bacteria and viruses. Strain records have (when available): * collection and isolation information * culturing medium recipes and growth conditions * photographs * GenBank accession link * collection site map * link to the taxonomic database Micro*scope The deposition of new strains are welcome if the strains are a valuable addition to the collection. Examples include strains that are referred to in publications, contain interesting molecular, biochemical or physiological properties, are the basis for taxonomic descriptions, are important for aquaculture, or are from an unusual geographical location or ecological habitat. The NCMA offers a course in phytoplankton culturing techniques and facilities for visiting scientists are available at the new laboratories in East Boothbay, Maine. Services include: Mass Culturing DNA and RNA, Purification, Private Holdings, Culture Techniques Course, Visiting Scientists, Single Cell Genomics, Flow Cytometry, Corporate Alliances and Technology Transfer.

Proper citation: National Center for Marine Algae and Microbiota (RRID:SCR_002120) Copy   

•   Source: SciCrunch Registry
  

https://www.humanbrainproject.eu/

Global, collaborative effort for neuroscience, medicine and computing to understand brain, its diseases and its computational capabilities. Goal is to obtain access to research, data sources, platforms and infrastructures offered by other organisations, and enabling organizations outside HBP to use HBP platforms to pursue their own research. Coordinating these activities is the responsibility of the European Research Programme.

Proper citation: Human Brain Project EU (RRID:SCR_002241) Copy   

•   Source: SciCrunch Registry
  

https://www.edx.org/

Massive, open, online courses (MOOCs) and interactive online classes in subjects including law, history, science, engineering, business, social sciences, computer science, public health, and artificial intelligence (AI). This non-profit was created by founding partners Harvard and MIT bringing the best of higher education to students around the world. Online courses are designed to be interesting, fun and rigorous. They are the best online courses, from the best professors and the best schools, spanning dozens of subjects. Some edX courses now offer ID verified Certificates of Achievement. A new way to demonstrate your achievement and showcase your knowledge.

Proper citation: edX (RRID:SCR_002240) Copy   

•   Source: SciCrunch Registry
  

http://figshare.com/articles/Tool_for_rapid_annotation_of_microbial_SNPs_TRAMS_a_simple_program_for_rapid_annotation_of_genomic_variation_in_prokaryotes_/782261

A software program for functional annotation of genomic single nucleotide polymorphisms (SNPs) which is available to download as a single file executable for WINDOWS users with limited computational experience and as a Python script for Mac OS and Linux users. It needs only a tab delimited text file containing SNP locations, reference nucleotide and SNPs in different strains along with a reference genome sequence in standard GenBank or EMBL format. It annotates SNPs as synonymous, non-synonymous or nonsense. Non-synonymous SNPs in start and stop codons are separated as non-start and non-stop SNPs, respectively. SNPs in overlapping features are annotated separately for each feature and multiple nucleotide polymorphisms (MNPs) within a codon are combined prior to annotation. A workflow has also been developed for use in Galaxy to map short reads to a reference genome and extract and annotate the SNPs.

Proper citation: TRAMS (RRID:SCR_002003) Copy   

•   Source: SciCrunch Registry
  

http://www.bioconductor.org/packages/release/bioc/html/TEQC.html

An R/Bioconductor package for quality assessment of target enrichment experiments. This package provides functionalities for assessing and visualizing the quality of the target enrichment process, like specificity and sensitivity of the capture, per-target read coverage and so on.

Proper citation: TEQC (RRID:SCR_001943) Copy   

•   Source: SciCrunch Registry
  

http://www.proteinlounge.com

Complete siRNA target database, complete Peptide-Antigen target database and a Kinase-Phosphatase database. They have also developed the largest database of illustrated signal transduction pathways, which are interconnected to their extensive protein database and online gene / protein analysis tools. The interactive web-based databases and software help life-scientists understand the complexity of systems biology. Systems biology efforts focus on understanding cellular networks, protein interactions involved in cell signaling, mechanisms of cell survival and apoptosis leading to development or identification of drug candidates against a variety of diseases. In the post-genomic era, one of the major concerns for life-science researchers is the organization of gene / protein data. Protein Lounge has met this concern by organizing all necessary data about genes / proteins into one portal.

Proper citation: Protein Lounge (RRID:SCR_002117) Copy   

•   Source: SciCrunch Registry
  

http://wiki.biac.duke.edu/jvs:cigal

Software program that provides accurate real-time stimulus control, behavioral and physiological recording, and synchronization with external devices. It can also provide continuous real-time feedback of task performance and physiological responses. Task programming typically involves a simple text file specifying basic parameter settings (e.g. screen color) and a list of stimulus events, which can include images, animated movies, sound files, text stimuli, video graphics, or commands that communicate with external hardware devices. Multiple video and auditory stimuli can be presented simultaneously. Multi-channel response recording and real-time feedback features require no user programming. Advanced users can add customized stimulus events using CIGAL's real-time programming capabilities. Output files can be automatically created in a variety of output formats (e.g. FSL 3-column files, XML Events files, CSV trial tables).

Proper citation: CIGAL (RRID:SCR_002232) Copy   

•   Source: SciCrunch Registry
  

http://cbi.nyu.edu/software/niftimatlab.php

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 28, 2025. Software tool that allows the user to operate on NIfTI image files from Matlab.

Proper citation: NIfTImatlab (RRID:SCR_002230) Copy   

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http://ncmir.ucsd.edu/downloads/jinx.shtm

Jinx was developed to aid in the 3D reconstruction of tomographic datasets acquired with one of the various electron microscopes available at the resource. Tomographic datasets consist of a series of 2D images from which objects of interest are segmented out for the 3D reconstruction. Jinx offers the user a graphical interface to step through each image of the series and facilities to manually trace out objects of interest. It relies on JadeDisplay to support the display of large images with graphical overlays and the JAI libraries for histogram functionality and other types of image manipulations. Jinx is currently under active development and future releases will offer semi-automated segmentation algorithms based on fuzzy logic, level set, and watershed algorithm. This software is free; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or any later version. See the GNU General Public License for more details. For a copy of the GNU General Public License, write to the Free Software Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307, USA. Sponsors: Jinx presented here was produced at the National Center for Microscopy and Imaging Research at San Diego, which is supported by the National Institutes of Health (NIH) through a National Center for Research Resources program grant P41 RR04050. open source license, GNU general public license

Proper citation: National Center for Microscopy and Imaging Research: Jinx (RRID:SCR_001939) Copy   

•   Source: SciCrunch Registry
  

https://www.nitrc.org/projects/uncbcp_4d_atlas/

Software package for constructing longitudinal atlases, which are the necessary steps for many brain-related applications.

Proper citation: 4D Atlases Construction (RRID:SCR_002227) Copy   

•   Source: SciCrunch Registry
  

https://neurograd.ucsd.edu/handbook/prog-requirement/comp-neuro/index.html

The Computational Neuroscience specialization is a new facet of the broader Neuroscience graduate program at UCSD. The goal of the specialization is to train the next generation of neuroscientists with the broad range of computational and analytical skills that are essential to understand the organization and function of complex neural systems. The specialization is intended for students with backgrounds in neuroscience, physics, chemistry, biology, psychology, computer science, engineering, and mathematics. This specialization allows Neuroscience students to concentrate on a focused program of rigorous course work in both the theoretical and experimental aspects of computational neuroscience. Students are encouraged to pursue thesis research that includes both an experimental and a computational component, often arranged by the student as a collaboration between two research groups. The program is focused on these major themes relevant for computational neuroscience research: - Neurobiology of Neural Systems - the anatomy, physiology, and behavior of systems of neurons, with emphasis on basic phenomenology. - Advanced Measurement Tools in Neuroscience - Advanced imaging and recording techniques reflecting the impact of experimental physics on neuroscience. - Algorithms for the Analysis of Neural Data - New algorithms and techniques for analyzing data obtained from physiological recording - Theoretical Basis for Collective Neural Dynamics - A synthesis of approaches from mathematics and physical sciences as well as biology will be used to explore the collective properties and nonlinear dynamics of neuronal systems. Sponsors: This program is supported by the University of California at San Diego.

Proper citation: University of California at San Diego Computational Neuroscience (RRID:SCR_001930) Copy   

•   Source: SciCrunch Registry
  

http://htslib.org/

Original SAMTOOLS package has been split into three separate repositories including Samtools, BCFtools and HTSlib. Samtools for manipulating next generation sequencing data used for reading, writing, editing, indexing,viewing nucleotide alignments in SAM,BAM,CRAM format. BCFtools used for reading, writing BCF2,VCF, gVCF files and calling, filtering, summarising SNP and short indel sequence variants. HTSlib used for reading, writing high throughput sequencing data.

Proper citation: SAMTOOLS (RRID:SCR_002105) Copy   

•   Source: SciCrunch Registry
  

http://pfind.ict.ac.cn/se/plink/

Software dedicated for the analysis of chemically cross-linked proteins or protein complexes using mass spectrometry., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: pFind Studio: pLink (RRID:SCR_000084) Copy   

•   Source: SciCrunch Registry
  

http://www.tm4.org/spotfinder.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Software designed for the rapid, reproducible and computer-aided analysis of microarray images and the quantification of gene expression.

Proper citation: Spotfinder (RRID:SCR_000085) Copy   

•   Source: SciCrunch Registry
  

http://bioinformatics.nyu.edu/Projects/GOALIE/

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. Generalized Ontological Algorithmic Logical Invariants Extractor (GOALIE) is a tool for the construction of time-course dependent enrichments. Requires an ODBC connection to an instance of the GO database. Platform: Windows compatible, Mac OS X compatible, Linux compatible

Proper citation: GOALIE (RRID:SCR_000088) Copy   

•   Source: SciCrunch Registry
  

https://simtk.org/home/aspf

Scalable particle fluid simulation code for Lagrangian particle-based fluid simulation. This adaptive sampling strategy allows using smaller (and thus more) particles in geometrically complex regions, while less particles are used for thick flat fluid volumes. Additionally, a novel distance-based particle surface definition is implemented which hides the particle granularity and allows dynamic resampling near the fluid-air interface. The code is implemented in C++ and should compile on Linux.

Proper citation: Adaptively Sampled Particle Fluids (RRID:SCR_000083) Copy   

•   Source: SciCrunch Registry
  

http://www.bioconductor.org/packages/release/bioc/html/ReQON.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Algorithm for recalibrating the base quality scores for aligned sequencing data in BAM format.

Proper citation: ReQON (RRID:SCR_000075) Copy   

•   Source: SciCrunch Registry
  

http://www.structbioinfor.org/cascleave2/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. A novel tool developed using Java program for the high-throughput in silico identification of substrate cleavage sites for various caspases from the amino acid sequences of the substrates.

Proper citation: Cascleave (RRID:SCR_000197) Copy   

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http://www.iro.umontreal.ca/~csuros/quadgt/

Software package for calling single-nucleotide variants in four sequenced genomes comprising a normal-tumor pair and the two parents. Genotypes are inferred using a joint model of parental variant frequencies, de novo germline mutations, and somatic mutations. The model quantifies the descent-by-modification relationships between the unknown genotypes by using a set of parameters in a Bayesian inference setting. Note that you can use it on any subset of the four related genomes, including parent-offspring trios, and normal-tumor pairs without parental samples.

Proper citation: QuadGT (RRID:SCR_000073) Copy   

•   Source: SciCrunch Registry
  

http://www.bioconductor.org/packages/release/bioc/html/HEM.html

Software package that fits heterogeneous error models for analysis of microarray data

Proper citation: HEM (RRID:SCR_000194) Copy   

•   Source: SciCrunch Registry