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http://wiki.c2b2.columbia.edu/honiglab_public/index.php/Software:DelPhi
DelPhi provides numerical solutions to the Poisson-Boltzmann equation (both linear and nonlinear form) for molecules of arbitrary shape and charge distribution. The current version is fast, accurate, and can handle extremely high lattice dimensions. It also includes flexible features for assigning different dielectric constants to different regions of space and treating systems containing mixed salt solutions. DelPhi takes as input a coordinate file format of a molecule or equivalent data for geometrical objects and/or charge distributions and calculates the electrostatic potential in and around the system, using a finite difference solution to the Poisson-Boltzmann equation. DelPhi is a versatile electrostatics simulation program that can be used to investigate electrostatic fields in a variety of molecular systems. Features of DelPhi include solutions to mixtures of salts of different valence; solutions to different dielectric constants to different regions of space; and estimation of the best relaxation parameter at run time.
Proper citation: DelPhi (RRID:SCR_008669) Copy
http://www.nitrc.org/projects/gscca_2013/
Group Sparse Canonical Correlation Analysis is a method designed to study the mutual relationship between two different types of data.
Proper citation: Group Sparse Canonical Correlation Analysis (RRID:SCR_014977) Copy
http://ccb.jhu.edu/software/hisat2/index.shtml
Graph-based alignment of next generation sequencing reads to a population of genomes.
Proper citation: HISAT2 (RRID:SCR_015530) Copy
Visualization and analysis software for interactive visual exploration and mining of fiber-tracts and brain networks with their genetic determinants and functional outcomes. BECA includes an fMRI and Diseases Analysis version as well as a Genome Explorer version.
Proper citation: BECA (RRID:SCR_015846) Copy
Software for semantic chemical editing, visualization, and analysis. It is designed for cross-platform use in computational chemistry, molecular modeling, bioinformatics, materials science, and related areas.
Proper citation: Avogadro (RRID:SCR_015983) Copy
http://plantgrn.noble.org/LegumeIP/
LegumeIP is an integrative database and bioinformatics platform for comparative genomics and transcriptomics to facilitate the study of gene function and genome evolution in legumes, and ultimately to generate molecular based breeding tools to improve quality of crop legumes. LegumeIP currently hosts large-scale genomics and transcriptomics data, including: * Genomic sequences of three model legumes, i.e. Medicago truncatula, Glycine max (soybean) and Lotus japonicus, including two reference plant species, Arabidopsis thaliana and Poplar trichocarpa, with the annotation based on UniProt TrEMBL, InterProScan, Gene Ontology and KEGG databases. LegumeIP covers a total 222,217 protein-coding gene sequences. * Large-scale gene expression data compiled from 104 array hybridizations from L. japonicas, 156 array hybridizations from M. truncatula gene atlas database, and 14 RNA-Seq-based gene expression profiles from G. max on different tissues including four common tissues: Nodule, Flower, Root and Leaf. * Systematic synteny analysis among M. truncatula, G. max, L. japonicus and A. thaliana. * Reconstruction of gene family and gene family-wide phylogenetic analysis across the five hosted species. LegumeIP features comprehensive search and visualization tools to enable the flexible query on gene annotation, gene family, synteny, relative abundance of gene expression.
Proper citation: LegumeIP (RRID:SCR_008906) Copy
Matlab toolbox that makes it easy to apply decoding analyses to neural data. The design of the toolbox revolves around four abstract object classes which enables users to interchange particular modules in order to try different analyses while keeping the rest of the processing stream intact. The toolbox is capable of analyzing data from many different types of recording modalities, and examples are given on how it can be used to decode basic visual information from neural spiking activity and how it can be used to examine how invariant the activity of a neural population is to stimulus transformations.
Proper citation: Neural Decoding Toolbox (RRID:SCR_009012) Copy
http://www.nitrc.org/projects/hdbig/
A collection of software tools for high dimensional brain imaging genomics. These tools are designed to perform comprehensive joint analysis of heterogeneous imaging genomics data. HDBIG-SR is an HDBIG toolkit for sparse regression while HDBIG-SCCA is an HDBIG toolkit for sparse association.
Proper citation: HDBIG (RRID:SCR_014120) Copy
http://www.nitrc.org/projects/cta_toolbox
A Matlab tool to perform statistical analysis on cortical thickness signals on brain surfaces obtained from Freesurfer. It is used for multi-resolutional analysis of such cortical thickness signals and detecting group differences. It is based on the Spectral Graph Wavelet Transform (SGWT) toolbox and provides plug and play methods for deriving Wavelet Multiscale Descriptor (WMD), cortical thickness smoothing using SGWT, Multivariate General Linear Model (MGLM), and False Discovery Rate (FDR).
Proper citation: Wisconsin Cortical Thickness Analysis (CTA) Toolbox (RRID:SCR_014180) Copy
http://krasnow1.gmu.edu/CENlab/software.html
Stochastic reaction-diffusion simulator in Java which is used for simulating neuronal signaling pathways.
Proper citation: NeuroRD (RRID:SCR_014769) Copy
https://github.com/brain-life/encode
Software that implements a framework to encode structural brain connectomes into multidimensional arrays (tensors). Encoding Connectomes provides an agile framework for computing over connectome edges and nodes.
Proper citation: Linear Fascicle Evaluation (RRID:SCR_016153) Copy
Open source software package for comparative sequence analysis using stochastic evolutionary models. Used for analysis of genetic sequence data in particular the inference of natural selection using techniques in phylogenetics, molecular evolution, and machine learning.
Proper citation: HyPhy (RRID:SCR_016162) Copy
http://www.nitrc.org/projects/psc/
Data analysis software that can simultaneously characterize a large number of white matter bundles within and across different subjects for group analysis. It has three major components: construction of the structural connectome for the whole brain, low-dimensional representation of streamlines in each connection, and multi-level connectome analysis.
Proper citation: Mapping Population-based Structural Connectomes (RRID:SCR_016232) Copy
Standard specification for organizing and describing outputs of neuroimaging experiments. Used to organize and describe neuroimaging and behavioral data by neuroscientific community as standard to organize and share data. BIDS prescribes file naming conventions and folder structure to store data in set of already existing file formats. Provides standardized templates to store associated metadata in form of Javascript Object Notation (JSON) and tab-separated value (TSV) files. Facilitates data sharing, metadata querying, and enables automatic data analysis pipelines. System to curate, aggregate, and annotate neuroimaging databases. Intended for magnetic resonance imaging data, magnetoencephalography data, electroencephalography data, and intracranial encephalography data.
Proper citation: Brain Imaging Data Structure (BIDs) (RRID:SCR_016124) Copy
Software toolkit for neuroelectrophysiology object modeling and data analysis in Python. Open source Python package for analysis of neuroelectrophysiology data.
Proper citation: nelpy (RRID:SCR_016209) Copy
https://github.com/ihmwg/IHM-dictionary
Software resource for a data representation for integrative/hybrid methods of modeling macromolecular structures.
Proper citation: IHM-dictionary (RRID:SCR_016186) Copy
Data repository for integrative/hybrid structural models of macromolecules and their assemblies. This includes atomistic models as well as multi-scale models consisting of different coarse-grained representations.
Proper citation: PDB-Dev (RRID:SCR_016185) Copy
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
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
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
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