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https://github.com/jf-lab/chendoscope

Software tool as part of CHEndoscope. Acquisition software that interfaces with CHEndoscope Ximea USB camera. This code is compatible with Linux and Windows systems.

Proper citation: chendoscope (RRID:SCR_021616) Copy   

•   Source: SciCrunch Registry

https://github.com/jamieboyd/AutoHeadFix

Software Python code for automated control of behavioural apparatus and imaging for mice in home cage environment.Part of Homecage Task Training and Mesoscale Imaging system.

Proper citation: AutoHeadFix (RRID:SCR_021617) Copy   

•   Source: SciCrunch Registry

https://github.com/bsbrl/craniobot

Software tool as part of Craniobot system.Generates, sends, and receives commands to communicate with the Craniobot.

Proper citation: craniobot (RRID:SCR_021609) Copy   

•   Source: SciCrunch Registry

https://murphylab.med.ubc.ca/automated-homecages/

Software tool as part of Automated Home Cage Functional Imaging system.

Proper citation: Automated Home-Cage Functional Imaging (RRID:SCR_021607) Copy   

•   Source: SciCrunch Registry

https://github.com/dublon/scintillate

Open source graphical viewer for time series calcium imaging evaluation and pre-processing.

Proper citation: Scintillate (RRID:SCR_021531) Copy   

•   Source: SciCrunch Registry

https://github.com/GuyButcher/alpha-helix-coordinate-frame-simulation

Source code for alpha-helix simulation framework written in Matlab. Specifically tested on Talin-1 Rod Domain.

Proper citation: alpha helix coordinate frame simulation (RRID:SCR_019320) Copy   

•   Source: SciCrunch Registry

https://github.com/ribeiro-lab/flyPAD-fpga

FPGA code for running main board of flyPAD. Code written in VHDL using Quartus 2 web edition software.

Proper citation: flyPAD (RRID:SCR_021522) Copy   

•   Source: SciCrunch Registry

https://github.com/tedinburgh/sepsis3-amsterdamumcdb

Repository contains files for implementing the Sepsis-3 definition in the freely-accessible Amsterdam University Medical Centers Database.

Proper citation: sepsis3-amsterdamumcdb (RRID:SCR_022042) Copy   

•   Source: SciCrunch Registry

https://github.com/HUST-NingKang-Lab/Meta-Prism-2.0

Software tool as microbial community sample search method based on smart pair wise sample comparison without compromising accuracy. Used as microbial communities similarites calculation and comparison tool.

Proper citation: Meta-Prism (RRID:SCR_021836) Copy   

•   Source: SciCrunch Registry

https://github.com/agneslandemard/naturalsounds_analysis

Software tool as source code for analyzing functional ultrasound data.

Proper citation: naturalsounds analysis (RRID:SCR_021793) Copy   

•   Source: SciCrunch Registry

http://www.computationalbioenergy.org/parallel-meta.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 30,2023. Open source pipeline for metagenomic data analysis, which enables efficient and parallel analysis of multiple metagenomic datasets and visualization of results for multiple samples. Can perform rapid data mining among microbial community data for comparative taxonomic and functional analysis.

Proper citation: Parallel-META (RRID:SCR_000121) 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.aetionomy.eu/

Consortium founded to establish mechanism-based taxonomies for Alzheimer's and Parkinson's disease and other neurodegenerative disorders (NDD), with the goal of facilitating development of more effective and targeted treatments. To do this, the consortium collects and analyzes data to: * Create new ways to combine underutilized data currently available in the literature, public databases, and from private companies * Determine how to dynamically organize and structure different types of knowledge about NDD * Determine how to apply this knowledge to construct new patient group classification * Identify correlations between disease features at molecular, tissue or organ-specific, and clinical levels * Identify sub-groups of patients based on the molecular cause of their disease, as opposed to the nature and location of their symptoms * Deliver data, tools, and recommendations for the biomedical community in the treatment of NDD A mechanism-based taxonomy is hoped to advance the: # Description and organization of the indication-specific data # Linking of data to disease models, based on causal and correlative relationships The expected outcome of AETIONOMY is a new NDD taxonomy system that distinguishes mixed pathologies, allowing for new features or classes to be added into the taxonomy, all with the goal of aiding drug and biomarker discovery.

Proper citation: AETIONOMY (RRID:SCR_000232) Copy   

•   Source: SciCrunch Registry

http://www.nationalmssociety.org/index.aspx

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Society helps people affected by Multiple Sclerosis by funding cutting-edge research, driving change through advocacy, facilitating professional education, and providing programs and services that help people with MS and their families move their lives forward.

Proper citation: National MS Society (RRID:SCR_000104) Copy   

•   Source: SciCrunch Registry

http://toc.lbg.ac.at/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. The projected cluster includes the LBIs for Applied Cancer Research, Clinical Oncology and Photodynamic Therapy, Gynecology and Gynecologic Oncology, Stem Cell Transplantation and Surgical Oncology. The aim of the projected cluster Translational Oncology is the cooperative investigation of genetic and molecular biological characteristics of the tumor cells involved in minimal residual disease (MRD) in vitro and translation of the experimental and diagnostic results into the clinical practice involving therapeutic modalities with the newest generation of antitumoral drugs. Minimal residual disease is the designation for the occurrence of a low number of tumor cells remaining clinically undetected following curative therapy that give rise to tumor relapses. MRD is a central question in cancer therapy, since a major subpopulation of patients which underwent curative resection and therapy ultimately relapse and would have received more aggressive adjuvant therapy, provided that residual disease had been clearly proven. Otherwise low-risk patients would have not been treated aggressively in an adjuvant setting. MRD can be detected by methods in bone marrow or by extremely sensitive PCR (polymerase-chain-reaction)-based methods in peripheral blood. PCR-based methods allow for the characterization of tumor-specific gene expression in circulating tumor cells and thereby provide additional information in regard to malignity of cells and prognosis. The different participating institutions have extensive experience in patient care, organization of clinical studies and laboratory investigation. In particular, expert knowledge in stem cell transplantation and histological detection of MRD, multicentric clinical testing of new anticancer drugs, specialized treatment of various selected tumor entities such as neuroendocrine tumors, gene expression analysis of circulating tumor cells and tumor signatures, and in vitro characterization of chemosensitivity as well as tumor cell biology have been acquired at the individual LBIs in the past and are complementary to each other to be combined in a larger cluster structure. The detection of circulating tumor cells will be supported by ongoing EU (OVCAD OVarian CAncer Diagnosis) and GenAU projects aiming at identification of ovarian cancer cells in the blood. The assessment of methylated DNA sequences (suppressor genes) in peripheral blood as an indicator of MRD can be performed with the help of OncoLab Diagnostics GmbH. Cooperative action in this cluster, using a common tumor bank/clinical data collection and the combined clinical and experimental efforts are the base for the execution of the presented MRD project.

Proper citation: Ludwig Boltzmann Cluster Translationale Onkologie (RRID:SCR_000020) Copy   

•   Source: SciCrunch Registry

http://deweylab.biostat.wisc.edu/rsem/

Software package for quantifying gene and isoform abundances from single end or paired end RNA Seq data. Accurate transcript quantification from RNA Seq data with or without reference genome. Used for accurate quantification of gene and isoform expression from RNA-Seq data.

Proper citation: RSEM (RRID:SCR_000262) Copy   

•   Source: SciCrunch Registry

http://teddy.epi.usf.edu/

International consortium of six centers assembled to participate in the development and implementation of studies to identify infectious agents, dietary factors, or other environmental agents, including psychosocial factors, that trigger type 1 diabetes in genetically susceptible people. The coordinating centers recruit and enroll subjects, obtaining informed consent from parents prior to or shortly after birth, genetic and other types of samples from neonates and parents, and prospectively following selected neonates throughout childhood or until development of islet autoimmunity or T1DM. The study tracks child diet, illnesses, allergies and other life experiences. A blood sample is taken from children every 3 months for 4 years. After 4 years, children will be seen every 6 months until the age of 15 years. Children are tested for 3 different autoantibodies. The study will compare the life experiences and blood and stool tests of the children who get autoantibodies and diabetes with some of those children who do not get autoantibodies or diabetes. In this way the study hopes to find the triggers of T1DM in children with higher risk genes.

Proper citation: TEDDY (RRID:SCR_000383) Copy   

•   Source: SciCrunch Registry

http://www.tarp.nih.gov/

Trans-NIH program encouraging and facilitating the study of the underlying mechanisms controlling blood vessel growth and development. Other aims include: to identify specific targets and to develop therapeutics against pathologic angiogenesis in order to reduce the morbidity due to abnormal blood vessel proliferation in a variety of disease states; to better understand the process of angiogenesis and vascularization to improve states of decreased vascularization; to encourage and facilitate the study of the processes of lymphangiogenesis; and to achieve these goals through a multidisciplinary approach, bringing together investigators with varied backgrounds and varied interests.

Proper citation: Trans-Institute Angiogenesis Research Program (RRID:SCR_000384) Copy   

•   Source: SciCrunch Registry

http://tomcat.esat.kuleuven.be/MACBETH/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 31, 2023. Web service for performing microarray classification. It aims at finding the best prediction among different classification methods by using randomizations of the benchmarking dataset.

Proper citation: M(at)CBETH (RRID:SCR_000265) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/mri_lbptop/

The packaged tools perform Local Binary Pattern on Three Orthogonal Planes (LBP-TOP) analysis on MR brain images. One can use them to extract LBP texture features for machine learning applications or other advance analysis. Bash scripts performing simple preprocessing with FSL and AFNI as well as LBP mapping programs written by Java are both including in this package. The output is the histogram describing the brain morphology.

Proper citation: Local Binary Pattern Analysis Tools for MR Brain Images (RRID:SCR_000412) Copy   

•   Source: SciCrunch Registry