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http://megasoftware.net/

Software integrated tool for conducting automatic and manual sequence alignment, inferring phylogenetic trees, mining web based databases, estimating rates of molecular evolution, and testing evolutionary hypotheses. Used for comparative analysis of DNA and protein sequences to infer molecular evolutionary patterns of genes, genomes, and species over time. MEGA version 4 expands on existing facilities for editing DNA sequence data from autosequencers, mining Web-databases, performing automatic and manual sequence alignment, analyzing sequence alignments to estimate evolutionary distances, inferring phylogenetic trees, and testing evolutionary hypotheses. MEGA version 6 enables inference of timetrees, as it implements RelTime method for estimating divergence times for all branching points in phylogeny.

Proper citation: MEGA (RRID:SCR_000667) Copy   

•   Source: SciCrunch Registry

https://3dvcell.ncbi.nlm.nih.gov/

THIS RESOURCE IS NO LONGER IN SERVICE, confirmed by curator 11/21/2018; Community of researchers attempting to build a comprehensive virtual cell model. The 3DVC will do for cell biology what the Large Hadron Collider (LHC) does for particle physics, but through a virtual rather than physical resource. It will bring together collaborators around a shared infrastructure to advance the field through efficient groundbreaking science and technology, the results of which will be broadly disseminated to an audience ranging from K12 to professionals. The 3DVC is committed to open science, yet strives for sustainability through new business models that leverages that open content.

Proper citation: 3DVC (RRID:SCR_001377) Copy   

•   Source: SciCrunch Registry

http://www.marine-geo.org/

Repository providing free access to marine geophysical data (e.g. bathymetry, seismic data, magnetics, gravity, images) and related land-based data from NSF-funded research conducted throughout the global oceans. Data Portals include GeoPRISMS, MARGINS, Ridge 2000, Antarctic and Southern Ocean Data Synthesis, the Global Multi-Resolution Topography Synthesis, and Seismic Reflection Field Data Portal. Primary data types served are multibeam bathymetric data from the ocean floor, seismic reflection data imaging below the seafloor, and multi-disciplinary ship based data from the Southern Ocean. Other holdings include deep-sea photographic transects, and ultra-high resolution bathymetry, temperature probe data, biological species compilations, MAPR and CTD data. Derived data products and sets include microseismicity catalogs, images, visualization scenes, magnetic and gravity compilations, grids of seismic layer thickness, velocity models, GIS project files, and 3D visualizations. Tools to discover, explore, and visualize data are available. They deliver catalogs, maps, and data through standard programmatic interfaces. GeoMapApp, a standalone data visualization and analysis tool, permits dynamic data exploration from a map interface and the capability to generate and download custom grids and maps and other data. Through GeoMapApp, users can access data hosted at the MGDS, at other data repositories, and import their own data sets. Global Multi-Resolution Topography (GMRT) is a continuously-updated compilation of seafloor bathymetry integrated with global land topography. It can be used to create maps and grids and it can be accessed through several standard programmatic interfaces including GeoMapApp and Google Earth. The GMRT compilation can also be explored in 3D using Virtual Ocean. The MGDS MediaBank contains high quality images, illustrations, animations and video clips that are organized into galleries. Media can be sorted by category, and keyword and map-based search options are provided. Each item in the MediaBank is accompanied by metadata that provides access to a cruise catalog and data repository.

Proper citation: Marine Geoscience Data System (RRID:SCR_002164) Copy   

•   Source: SciCrunch Registry

https://masst.gnps2.org/microbemasst/

Web taxonomically informed mass spectrometry search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging database of over 60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns.

Proper citation: microbeMASST (RRID:SCR_024713) Copy   

•   Source: SciCrunch Registry

http://www.sb.cs.cmu.edu/drem

The Dynamic Regulatory Events Miner (DREM) allows one to model, analyze, and visualize transcriptional gene regulation dynamics. The method of DREM takes as input time series gene expression data and static transcription factor-gene interaction data (e.g. ChIP-chip data), and produces as output a dynamic regulatory map. The dynamic regulatory map highlights major bifurcation events in the time series expression data and transcription factors potentially responsible for them. DREM 2.0 was released and supports a number of new features including: * new static binding data for mouse, human, D. melanogaster, A. thaliana * a new and more flexible implementation of the IOHMM supports dynamic binding data for each time point or as a mix of static/dynamic TF input * expression levels of TFs can be used to improve the models learned by DREM * the motif finder DECOD can be used in conjuction with DREM and help find DNA motifs for unannotated splits * new features for the visualization of expressed TFs, dragging boxes in the model view, and switching between representations

Proper citation: Dynamic Regulatory Events Miner (RRID:SCR_003080) Copy   

•   Source: SciCrunch Registry

http://www.cs.cmu.edu/~jernst/stem/

The Short Time-series Expression Miner (STEM) is a Java program for clustering, comparing, and visualizing short time series gene expression data from microarray experiments (~8 time points or fewer). STEM allows researchers to identify significant temporal expression profiles and the genes associated with these profiles and to compare the behavior of these genes across multiple conditions. STEM is fully integrated with the Gene Ontology (GO) database supporting GO category gene enrichment analyses for sets of genes having the same temporal expression pattern. STEM also supports the ability to easily determine and visualize the behavior of genes belonging to a given GO category or user defined gene set, identifying which temporal expression profiles were enriched for these genes. (Note: While STEM is designed primarily to analyze data from short time course experiments it can be used to analyze data from any small set of experiments which can naturally be ordered sequentially including dose response experiments.) Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: Short Time-series Expression Miner (STEM) (RRID:SCR_005016) Copy   

•   Source: SciCrunch Registry

http://www.autopack.org/

An open-source general packing algorithm that packs 3D objects onto surfaces, into volumes, and around volumes. It provides a general architecture to allow various packing algorithms to interoperate efficiently in the same model. autoPack can incorporate any packing solution into its modular python program architecture, but is currently optimized to provide a novel solution to the loose packing problem which places objects of discrete size into place (compared to advancing front, popcorn, or other fast tight-packing solutions that allow objects to scale to arbitrary masses.) Most popular 3D software programs now contain robust physics engines based on Bullet that can separate small collections of overlapping objects or allow volumes to be filled by pouring shapes from generators, but these approaches fails for large complex systems and result in either overlapping geometry, crashed software, or non-random gradients. Most packing algorithms are designed to position objects as efficiently as possible, but autoPack allows the user to select from random loose packing to highly organized packing methods����??even to choose both methods at the same time. autoPack positions 3D geometries into, onto, and around volumes with minimal to zero overlap. autoPack mixes several packing approaches and procedural growth algorithms. autoPack can thus place objects with forces and constraints to allow a high degree of control ranging from completely random distributions to highly ordered structures. * zero to minimal overlaps depending on the method used * accuracy vs speed parameters selected by the user * zero edge effects * complete control, from fully random to fully ordered distributions * agent-based interaction, weighting, and collision control

Proper citation: Autopack (RRID:SCR_006830) Copy   

•   Source: SciCrunch Registry

https://github.com/oushujun/LTR_retriever

Software package for identification of long terminal repeat retrotransposons (LTR-RTs). Removes false positives from initial software predictions. Achieves very high specificity, accuracy, and precision without significantly sacrificing sensitivity, hence significantly outperforming existing methods. Can construct LTR libraries directly from self-corrected PacBio reads prior to genome assembly.

Proper citation: LTR_retriever (RRID:SCR_017623) Copy   

•   Source: SciCrunch Registry

http://www.pondr.com/

Web tool to predict order and disorder from amino acid sequence. Used to predict of natural disordered regions in proteins.

Proper citation: PONDR (RRID:SCR_023691) Copy   

•   Source: SciCrunch Registry

http://www.sb.fsu.edu/~rsref/Distribution/roadmap_distribution.htm

Software tool to display surface of macromolecule and its properties. Uses projections to map van der Waals or solvent accessible surface of macromolecule onto plane., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Roadmap (RRID:SCR_017207) Copy   

•   Source: SciCrunch Registry

https://www.ezbiocloud.net/tools/orthoaniu

Software tool for calculating average nucleotide identity.

Proper citation: OrthoANIu (RRID:SCR_022562) Copy   

•   Source: SciCrunch Registry

http://www.pyrosetta.org/

Interactive Python based interface to Rosetta molecular modeling suite. Stand alone Python based implementation of Rosetta molecular modeling package that allows users to write custom structure prediction and design algorithms using major Rosetta sampling and scoring functions.

Proper citation: PyRosetta (RRID:SCR_018541) Copy   

•   Source: SciCrunch Registry

https://github.com/raphael-group/chisel

Software tool to infer allele and haplotype specific copy numbers in individual cells from low coverage single cell DNA sequencing data. Integrates weak allelic signals across individual cells, powering strength of single cell sequencing technologies to overcome weakness. Includes global clustering of RDRs and BAFs, and rigorous model selection procedure for inferring genome ploidy that improves both inference of allele specific and total copy numbers.

Proper citation: CHISEL (RRID:SCR_023220) Copy   

•   Source: SciCrunch Registry

https://redu.ucsd.edu/

Software framework to find and re-analyze public Mass Spectrometry data. Used to find uniformly formatted public MS/MS data in the Global Natural Product Social Molecular Networking Platform (GNPS) via formatted metadata. New or previously collected data can be added provided they adhere to the ReDU metadata standards (the implemented drag-and-drop validator is applicable to any scientific data) and data are available in GNPS/MassIVE.

Proper citation: ReDU (RRID:SCR_025105) Copy   

•   Source: SciCrunch Registry

http://www.cise.ufl.edu/~tichen/ShapeComplexAtlas.zip

A Matlab demo for constructing a neuro-anatomical shape complex atlas from 3D MRI brain structures, based on the paper Ting Chen, Anand Rangarajan, Stephan J. Eisenschenk and Baba C. Vemuri, Construction of a Neuroanatomical Shape Complex Atlas from 3D MRI Brain Structures. In NeuroImage, Volume 60, Page 1778-1787, 2012

Proper citation: ShapeComplexAtlas (RRID:SCR_002553) Copy   

•   Source: SciCrunch Registry

http://www.algalresourcescollection.com/

Supplier of algae strains that aims to be a resource to both the HAB research community and biotechnological applications. Researchers can order and deposit strains with the ARC.

Proper citation: Algal Resources Collection (RRID:SCR_014942) Copy   

•   Source: SciCrunch Registry

http://wings-workflows.org

A software application which assists scientists with designing computational experiments. WINGS is a semantic workflow system which incorporates semantic constraints about datasets and workflow components into its workflow representations. The workflow system has an open modular design and can be easily integrated with other existing workflow systems and execution frameworks to extend them with semantic reasoning capabilities. WINGS also allows users to express high-level descriptions of their analysis goals, and assists them by automatically and systematically generating possible workflows that are consistent with that request. In cases where privacy or off-line use are important, WINGS can submit workflows in a scripted format for execution in the local host. It uses Pegasus or OODT as the execution engine for large-scale distributed workflow execution.

Proper citation: WINGS (RRID:SCR_013997) Copy   

•   Source: SciCrunch Registry

http://animatlab.com/

A software tool that combines biomechanical simulation and biologically realistic neural networks to create realistic models of, and perform tests on, biomechanical workings. AnimatLab was primarily designed to model and test the operation of neural circuits that might produce behavior patterns observed in an intact animal. Users can create an animalistic or robotic body and place it in a virtual environment with physics that are accurate and realistic. Users can then design a nervous system that controls the behavior of the body within the physically realistic environment. Various models for different types of actions, builds, and movements are available.

Proper citation: AnimatLab (RRID:SCR_014252) Copy   

•   Source: SciCrunch Registry

http://neurodata.io/

Project portal dedicated to understand animal and machine intelligence and repository of data and tools. Suite of tools to analyze and graph imaging data. Image and data repository for large, publicly available neuro-specific data files and images. Contains tools for analytics, databases, cloud computing, and Web-services applied to both big neuroimages and big neurographs.

Proper citation: neurodata (RRID:SCR_014264) Copy   

•   Source: SciCrunch Registry

http://fatcat.burnham.org/

Web server for flexible protein structure comparison. Structure alignment is formulated as the aligned fragment pairs chaining process allowing at most t twists, and the flexible structure alignment is transformed into a rigid structure alignment when t is forced to be 0., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: FATCAT (RRID:SCR_014631) Copy   

•   Source: SciCrunch Registry