National Centers for Systems Biology

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The National Centers for Biomedical Computing (NCBC) has created a system called Biositemaps to allow scientists to announce the existence of resources such as software, data, materials and services, as well as discover and utilize the resources published by others. National Centers of Systems Biology researchers are working with the NCBC to publish all public resources through Biositemaps. Below you can search and browse these resources.

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Below is a table containing all National Centers of Systems Biology resources from the Biositemaps database, for those who would prefer to browse.

Name Description Organization Center Contact
A survey of gene expression in 17 mouse tissues with biological replication A tissue survey was performed examining gene expression profiles across 17 mouse tissues. The unique feature of this tissue survey is that 5 biological (mouse) replicates were profiled individually, as opposed to hybridizing a pool of their RNA samples to microarrays. The Jackson Laboratory Center for Genome Dynamics Imogen Hurley
Accelerated Stochastic Simulation Algorithm for Reaction Networks This is an exact method for stochastic simulation of chemical reaction networks (Exact R-Leap) to accelerate the Stochastic Simulation Algorithm (SSA). University of California Irvine Center for Complex Biological Systems Eric Mjolsness
Adhesome Literature-based protein-protein interaction network extracted from publications describing functional interaction in adhesion complexes of mammalian cells. Mount Sinai School of Medicine, Ma’ayan Laboratory Systems Biology Center New York Avi Ma’ayan
Advanced Correlation Techniques Group Working group to discuss research advances and applications related to correlation techniques in advanced microscopy imaging tools. University of California Irvine Center for Complex Biological Systems Michelle Digman
Affymetrix expression data used to estimate p-values in small microarray experiments Microarray data typically have small numbers of observations per gene, which can result in low power for statistical tests. We investigated permutation based methods for estimating p-values. The Jackson Laboratory Center for Genome Dynamics Imogen Hurley
Arabidopsis-Indel-Array genotyping array built with 70-mer oligonucleotide elements representing insertion/deletion (indel) polymorphisms between the Arabidopsis thaliana accessions Columbia-0 (Col) and Landsberg erecta (Ler). This array assesses 240 unique markers in a single hybridization experiment at a cost of less than $50 in materials per line. Harvard FAS Center for Systems Biology Center for Modular Biology Christine Queitsch
Architecture of energy balance traits in emerging lines of the Collaborative Cross: 15 metabolism- and exercise-related phenotypes The Collaborative Cross (CC) recombinant inbred panel was conceived as an improved resource for mammalian systems genetics and to overcome many of the limitations of traditional QTL mapping populations. To investigate the utility and insights that can be learned from the CC, experiments were performed involving incipient CC lines that had undergone at least five generations of inbreeding (pre-CC). Pre-CC lines were involved in four distinct phenotyping arms, then genotyped on a high-density Affymetrix platform. In this study, we characterized phenotypic variation and mapped QTL in the pre-CC population for a suite of traits revolving around energy balance, including body weight and body composition both before and after a 12-day period of voluntary exercise in running wheels. The Jackson Laboratory Center for Genome Dynamics Imogen Hurley
Automated Particle Tracking and Analysis A LabView module to allow particle tracking in time-stack images. University of California Irvine Center for Complex Biological Systems Steve Gross
AVIS The AVIS Viewer is a visualization tool for viewing and sharing intracellular signaling, gene regulation and protein interaction networks. AVIS is implemented as an AJAX enabled syndicated Google gadget. It allows any webpage to render an image from a text file representation of signaling, gene regulatory or protein interaction networks Mount Sinai School of Medicine, Ma’ayan Laboratory Systems Biology Center New York Avi Ma’ayan
Background removal, registration and averaging of quantitative gene expression data BREReA package is designed to remove background from the one-dimensional patterns of segmentation gene expression in the early Drosophila embryo, to register them to reduce the variation in domain positions and to produce the reference data. The rationale behind this approach is the relative independence of segmentation gene expression from genes controlling the dorsoventral (D-V) patterning of the embryo. This allows us to consider the expression of segmentation genes in one dimension along the AP axis, which is a level of representation suitable for answering many important biological questions. The University of Chicago Chicago Center for Systems Biology John Reinitz
Banjo: Bayesian Network Inference with Java Objects Banjo is a highly efficient, configurable, and extensible software package for the inference of either static or dynamic Bayesian networks. Duke University Center for Systems Biology, Durham, NC Alex Hartemink
Bayesian Factor Regression Models Statistical software for modelling and analysis of sparse latent factor models, pathway analysis and predictive modelling with large-scale gene expression data sets. Duke University Center for Systems Biology, Durham, NC Mike West
BioNetGen A general-purpose tool for computer-aided generation of rule-based deterministic or stochastic models of chemical reaction systems. University of New Mexico New Mexico Spatio Temporal Modeling Center, Albuquerque, New Mexico Bill Hlavacek, James Faeder
Body composition and bone density data from SM x NZB and NZB x RF mouse intercross populations Measurements of body weight, four different fat pad weights, bone mineral density and bone geometry were taken from SM x NZB and NZB x RF mouse intercross populations. The Jackson Laboratory Center for Genome Dynamics Imogen Hurley
Cancer-Module-Map “Web access to comprehensive modular analysis of transcriptional responses in human cancer, including the full cancer expression compendium, detailed clinical annotations, and all the significant modules. Various searching, browsing and visualization capabilities are provided.” Harvard FAS Center for Systems Biology Center for Modular Biology Aviv Regev
CELL DYNAMICS CORE The Cell Dynamics Core develops technology and protocols for live cell imaging in dynamically changing environments. Fluorescent reporters allow for dynamic data acquisition, microfluidic devices allow users to determine the dynamically changing environment, and live cell microscopy and automated image analysis allows for quantitative dynamic data over long timecourse.The Core provides microfluidic chips and master molds based on pre-designed masks or user designs, and facilities for live cell imaging in dynamically changing environment. In addition, the core assists users in fluorescent reporter designs, the conception of microfluidic designs, the implementation of microfabrication technology, fluorescent-reporter quantification, automated live-cell imaging, and computer-assisted image processing. SDCSB San Diego Center for Systems Biology SDCSB Coordinator
Cell_Span A GUI frontend for the R statistics package that computes Hopkins and Ripley statistics from spatial patterns of nanoparticles. University of New Mexico New Mexico Spatio Temporal Modeling Center, Albuquerque, New Mexico Stanly Steinberg, Michael Wester
CellNetOptimizer MATLAB toolbox for creating logic-based models of signal transduction networks, and training them agains high-throughput biochemical data Harvard Medical School/ M.I.T. Center for Cell Decision Processes, Boston, MA Julio Saez-Rodriguez
CellTracer Integrated graphical user interface for automating cell segmentation/lineage reconstruction. Designed for biologists to extract single cell information from their microscopy images. Duke University Center for Systems Biology, Durham, NC Mike West
CGDSNP Center for Genome Dynamics SNP Database (CGDSNP) is a high quality single nucleotide polymorphism (SNP) database with more than 8 Million SNPs from 74 strains of laboratory mice, drawn from several sources. The Jackson Laboratory Center for Genome Dynamics Imogen Hurley
Coordinated Expression Domains in Mammalian Genomes Genes showing similar expression patterns are often clustered along the genome. We demonstrate the existence of correlated expression across multiple scales, from neighboring genes to chromosomal domains that span tens of megabases and, in some cases, entire chromosomes. The Jackson Laboratory Center for Genome Dynamics Imogen Hurley
CRNSimulator Many mathematical models in biology are described by ordinary differential equations, often derived from mass-action or Michaelis-Menten chemical kinetics. This is a Mathematica package for the syntactic manipulation of chemical reaction networks as Mathematica expressions, and for the simulation of such systems. It is particularly well-suited for engineered chemical systems, in which chemical reaction networks can be used as a kind of “programming language”. This resource was created by David Soloveichik. UCSF Center for Systems and Synthetic Biology David Soloveichik
DataRail Open source MATLAB toolbox for managing, transforming, visualizing, and modeling data, in particular the high-throughput data encountered in Systems Biology,. Harvard Medical School/ M.I.T. Center for Cell Decision Processes, Boston, MA Julio Saez-Rodriguez
Diversity Outcross (DO) QTL Mapping data – coat color, serum cholesterol, high fat diet A panel of 141 male and female Diversity Outcross (DO) mice were phenotyped over a period of 24 weeks. Half of the mice were fed a chow diet and half were fed a high fat diet. Coat color was recorded and serum cholesterol was measured at two time points (8 and 24 weeks). The mice were genotyped using the Mouse Universal Genotyping Array and a hidden Markov model was used to infer founder Array for each sample. These inferred Array were condensed to eight founder genotype probabilities at each locus and a linear model was fit (using sex and diet as covariates) at each marker. The Jackson Laboratory Center for Genome Dynamics Imogen Hurley
DOQCS “A repository of models of signaling pathways. It includes reaction schemes, concentrations, rate constants, as well as annotations on the models. The database provides a range of search, navigation, and comparison functions.” National Center for Biological Sciences, Bhalla Laboratory, India Systems Biology Center New York Upindar Bhalla
Dynetica Gene circuit simulation software for graphical construction of kinetic models and automatic generation of the implied differential equations, time course simulations using deteriministic or stochastic algorithms, and sensitivity analyses. Duke University Center for Systems Biology, Durham, NC Lingchong You
Eight-strain diallel from establishment of Collaborative Cross – Blood composition, blood pressure, plasma chemistries, electrocardiography, densiometry and body composition The classic diallel takes a set of parents and produces offspring from all possible mating pairs. Phenotype values among the offspring can then be related back to their respective parentage. When the parents are diploid, sexed, and inbred, the diallel can characterize aggregate effects of genetic background on a phenotype, revealing effects of strain dosage, heterosis, parent of origin, epistasis, and sex-specific versions thereof. We present a data set of 48 phenotypes collected from an incomplete eight-strain diallel that arose serendipitously from the establishment of the Collaborative Cross (Churchill et al. 2004; Chesler et al. 2008; Collaborative Cross Consortium 2012). The Jackson Laboratory Center for Genome Dynamics Imogen Hurley
EMBER EMBER is a tool for combining gene expression and binding data to identify gene targets of transcription factor binding events based on expression patterns. It is described in Maienschein-Cline, M., Zhou, J., White, K. P., Sciammas, R. & Dinner, A. R. Discovering transcription factor regulatory targets using gene expression and binding data. Bioinformatics, 28, 206-213 (2012).
PMID: 22084256 PMCID: PMC3259433
The University of Chicago Chicago Center for Systems Biology Aaron Dinner
ESCAPE ESCAPE is a mammalian embryonic stem cell specific database (Embryonic Stem Cell Atlas from Pluripotency Evidence). The database was created by collecting and integrating data reporting results from various published studies that profiled human and mouse ESCs including: protein-DNA binding interactions extracted from ChIP-seq/chip experiments, gene regulatory interactions from loss/gain-of-function studies followed by genome-wide mRNA expression profiling, protein interactions from immunoprecipitation followed by mass-spectrometry proteomics, a list of potential pluripotency regulators from RNA interference screens, ESC-specific proteins and phosphoproteins with specified phosphosites from proteomics and phosphoproteomics studies, time-course genome-wide mRNA microarray datasets from differentiating mouse ESCs, and histone modification status from genome-wide studies. Mount Sinai School of Medicine, Ma’ayan Laboratory Systems Biology Center New York Avi Ma’ayan
Expression2Kinases “Expression2Kinases (X2K) is a method to identify upstream regulators likely responsible for observed patterns in genome-wide gene expression. By integrating ChIP-seq/chip and position-weight-matrices (PWMs) data, protein-protein interactions, and kinase-substrate phosphorylation reactions X2K can better identify regulatory mechanisms upstream of genome-wide differences in gene expression. X2K first infers the most likely transcription factors that regulate the differences in gene expression, then use protein-protein interactions to connect the identified transcription factors using additional proteins for building transcriptional regulatory subnetworks centered on these factors, and finally use kinase-substrate protein phosphorylation reactions, to identify and rank candidate protein-kinases that most likely regulate the formation of the identified transcriptional complexes.” Mount Sinai School of Medicine, Ma’ayan Laboratory Systems Biology Center New York Avi Ma’ayan
FNV Written in Adobe ActionScript 3.0 the viewer accepts simple Extensible Markup Language (XML) formatted input files to display pathways in vector graphics Mount Sinai School of Medicine, Ma’ayan Laboratory Systems Biology Center New York Avi Ma’ayan
Fungal-Orthogroup-Repository provides the orthogroup assignments for all predicted protein-coding genes across 23 Ascomycete fungal genomes. Harvard FAS Center for Systems Biology Center for Modular Biology Ilan Wapinski
GATE GATE is a software system used to analyze time-series expression data. It creates cluster files from time-series data for visualization as movies. It used prior knowledge interaction networks and gene-lists libraries for identification of biological themes identified using the clustering analysis. Mount Sinai School of Medicine, Ma’ayan Laboratory Systems Biology Center New York Avi Ma’ayan
Gaussian Graphical Models Statistical software for Bayesian analysis and search of graphical/network structures in the framework of Gaussian graphical models, with links to applications in gene expression studies. Duke University Center for Systems Biology, Durham, NC Mike West
Gene expression response to diet in a strain survey Gene expression was compared between mice from 12 inbred strains who were fed either a standard or atherogenic high-fat diet. The Jackson Laboratory Center for Genome Dynamics Imogen Hurley
Gene Network Inference Provides Objective-C (Cocoa for Mac, GNUstep for Linux/Windows) optimization framework to learn linear gene regulatory networks from various types of gene expression data. The optimization incorporates network sparsity constraint through L1 regularization as well as incorporation of existing network information. The framework can handle wild type, perturbation, gene knockout and heterozygous knockdown gene expression data. University of California Irvine Center for Complex Biological Systems Qing Nie
Genes2FANs Genes2FANs is a web based tool and a database that utilizes 14 carefully constructed FANs and a large-scale protein-protein interaction (PPI) network to build subnetworks that connect input lists of human and mouse genes. The FANs are created from mammalian gene set libraries where mouse genes are converted to their human orthologs. The tool takes as input a list of human or mouse Entrez gene symbols to produce a subnetwork and a ranked list of intermediate genes that are used to connect the query input list. In addition, users can enter any PubMed search term and then the system automatically converts the returned results to gene lists using GeneRIF. This gene list is then used as input to generate a subnetwork from the user’s PubMed query. Mount Sinai School of Medicine, Ma’ayan Laboratory Systems Biology Center New York Avi Ma’ayan
Genes2Networks “Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from “”seed”" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list.” Mount Sinai School of Medicine, Ma’ayan Laboratory Systems Biology Center New York Avi Ma’ayan
Genetic analysis of complex traits in the emerging collaborative cross: white spot, body weight and liver gene expression The Collaborative Cross (CC) recombinant inbred panel was conceived as an ideal resource for mammalian system genetics. The pre-Collaborative Cross (pre-CC) is a proof-of-concept experiment involving CC lines that have undergone at least five generations of inbreeding. Pre-CC mice are partially inbred strains created by intercrossing eight founder (parental) strains. The genetic profile of these emerging lines reveals high diversity, balanced allele frequencies, and well-distributed recombination – all ideal qualities for a mapping panel. We have mapped white spot, a discrete trait; body weight, a highly polygenic complex trait; and more than 11,000 liver gene expression traits. The Jackson Laboratory Center for Genome Dynamics Imogen Hurley
Genetic analysis of hematological parameters in incipient lines of the Collaborative Cross We used a newly developed mouse resource population, the Collaborative Cross (CC), to identify genetic determinants of hematological parameters. We surveyed the eight founder strains of the CC and performed a mapping study using 131 incipient lines of the CC. Genome scans identified quantitative trait loci for several hematological parameters. The Jackson Laboratory Center for Genome Dynamics Imogen Hurley
Genetic Circuit Code The following archives contain source code for numerically integrating gene circuit models, for evaluating the least-squares score of a gene circuit compared to data, and for gene circuit optimization by Serial and Parallel Lam Simulated Annealing. The archives also contain Perl and Bourne shell scripts for gene circuit analysis.
PMID: 15342511 PMCID: PMC1471003
PMID: 15254541
The University of Chicago Chicago Center for Systems Biology John Reinitz
Genome Interval Overlap Calculator Genome Interval Overlap Calculator is a general purpose application for calculating the interval-by-interval overlap between two input files. One use of this application is to use the output from the Mouse Indentical by Decent tool to “filter out” regions of the genome that are identical between two strains. This could be applied to QTLs, gene lists etc The Jackson Laboratory Center for Genome Dynamics Imogen Hurley
Genome-wide association mapping of quantitative traits in NMRI outbred mice Our genome wide assoication study using 288 outbred NMRI mice was performed to map loci influencing HDL cholesterol, systolic blood pressure, triglyceride levels, glucose, and urinary albumin-to-creatinine ratios. The Jackson Laboratory Center for Genome Dynamics Imogen Hurley
Globals for Images Software analysis tools for image files derived from multiple spectroscopic techniques. University of California Laboratory for Fluorescence Imaging Tracey Scott
Gold_Code A MATLAB package for computing Hopkins and Ripley statistics from spatial patterns of nanoparticles and making plots of particle clusters. University of New Mexico New Mexico Spatio Temporal Modeling Center, Albuquerque, New Mexico Stanly Steinberg, Michael Wester
GPU Codes for 3D Modeling Provides CUDA code for Nvidia GPUs of a 3D model of epidermal development. The model includes GPU implementation of the subcellular element method for 3D spatial cells, an intracellular gene network for each cell represented by a set of ODEs, cell-cell neighbor communication through Notch signaling as part of each cell’s internal gene network, and cell behaviors of growth and division. University of California Irvine Center for Complex Biological Systems Qing Nie
GPU software Statistical software for massively parallel GPU-based computing, enabling mixture modeling of massive datasets possible on one computer. Duke University Center for Systems Biology, Durham, NC Mike West
Graph Explore Software for dynamically displaying, exploring and modifying large graphs and networks, with a range of visualisation and interactive analysis facilities. Duke University Center for Systems Biology, Durham, NC Mike West
Graphical tool for regulatory and evolutionary analysis of enhancers This is a python plotting tool for use in analyzing the transcriptional model as well as evolutionary paths. It can take a set of optimized transcriptional model parameters and plot the predicted and observed mRNA expression data of the constructs, predicted binding sites, PWM scores, and specific information relating to individual regulatory mechanisms. It can also use the NEEA paths and plot out each of the aforementioned information at each point along the trajectory. The University of Chicago Chicago Center for Systems Biology John Reinitz
High-fat diet leads to tissue-specific changes reflecting risk factors for diseases in DBA/2J mice The aim of this study was to characterize the responses of individual tissues to high-fat feeding as a function of mass, fat composition, and transcript abundance. We examined a panel of eight tissues [5 white adipose tissues, brown adipose tissue, liver, muscle] obtained from DBA/2J mice on either a standard breeding diet or a high-fat diet. The Jackson Laboratory Center for Genome Dynamics Imogen Hurley
Imputed Genotype Resource – 74 inbred mouse strains (Szatkiewicz et al. 2008) We have created a high-density SNP resource encompassing 7.87 million polymorphic loci across 74 inbred mouse strains of the laboratory mouse by combining data available from public databases and training a hidden Markov model to impute missing genotypes in the combined data The Jackson Laboratory Center for Genome Dynamics Imogen Hurley
Imputed Mouse SNP Resource Imputed Mouse SNP Resource includes full-genome genotype imputations for 88 classical laboratory mouse strains. The tools allow you to filter the full data set down to a particular set of strains and region of interest. You can view the distribution of imputation confidence for the selected strains averaged over your region of interest and then download the filtered data. The Jackson Laboratory Center for Genome Dynamics Imogen Hurley
In silico haplotype association mapping in laboratory mice – high density lipoprotein cholesterol (HDL) and red blood cell count (RBC) To assess the utility of haplotype association mapping (HAM) as a quantitative trait locus (QTL) discovery tool, we conducted HAM analyses for red blood cell count (RBC) and high density lipoprotein cholesterol (HDL) in mice. We then experimentally tested each HAM QTL using published crosses or new F2 intercrosses guided by the haplotype at the HAM peaks The Jackson Laboratory Center for Genome Dynamics Imogen Hurley
Indicator-Vectors “The indicator vectors preserved DNA character information and provided quantitative measures of correlations among taxonomic groups. This method is scalable to the largest datasets envisioned in this field, provides a visually-intuitive display that captures relational affinities derived from sequence data across a diversity of life forms, and is potentially a useful complement to current tree-building techniques for studying evolutionary processes based on DNA data.” Mount Sinai School of Medicine, Sirovich Laboratory Systems Biology Center New York Lawrence Sirovich
Individual Variation Microarray Experiment in 12 male mice This experiment was designed to assess transcript abundance variation in mice under normal lab conditions. Four tissues were sampled from twelve 10-week old male mice. The Jackson Laboratory Center for Genome Dynamics Imogen Hurley
iScMid Literature-based protein-protein and gene-regulatory interactions extracted from publication describing interactions in mouse and human embryonic stem cells. Mount Sinai School of Medicine, Ma’ayan Laboratory Systems Biology Center New York Avi Ma’ayan
KEA Kinase enrichment analysis (KEA) is a web-based tool with an underlying database providing users with the ability to link lists of mammalian proteins/genes with the kinases that phosphorylate them. The system draws from several available kinase-substrate databases to compute kinase enrichment probability based on the distribution of kinase-substrate proportions in the background kinase-substrate database compared with kinases found to be associated with an input list of genes/proteins. Mount Sinai School of Medicine, Ma’ayan Laboratory Systems Biology Center New York Avi Ma’ayan
Laboratory of Fluorescence Dynamics The Laboratory for Fluorescence Dynamics (LFD) is a national research resource center for biomedical fluorescence spectroscopy. The LFD’s main activities are i) Services and Resources for state-of-the-art fluorescence measurements, microscopy and spectroscopy, ii) Research and Development to design, test, and implement advances in the technology of hardware, software, and biomedical application, and iii) Training and Dissemination of knowledge relevant to fluorescence spectroscopic principles, instrumentation, and applications. University of California Irvine Center for Complex Biological Systems Enrico Gratton
Lists2networks Lists2Networks is a web-based software system used to analyze lists of mammalian genes. It creates a similarity matrix for many uploaded lists and compares the resultant lists to libraries of gene-lists from different categories. Users can create networks of lists and expand lists with prior knowledge networks such as protein-protein interactions, co-expression or co-annotation networks. Mount Sinai School of Medicine, Ma’ayan Laboratory Systems Biology Center New York Avi Ma’ayan
Mapping-Mutations-in-Yeast Software for using microarray data on DNA hybridization to detect single feature polymorphisms (SFP) and use them to map genetic traits in crosses between different strain backgrounds. Harvard FAS Center for Systems Biology Center for Modular Biology “Ayellet Segre, Andrew Murray”
MATHEMATICAL MODELING CORE A key goal of Systems Biology is the predictive understanding of the multi-component biological system or network. This entails the formulation of hypothesis and conclusions not only in the form of words or diagrams but using the language of Math. The mission of the Mathematical Modeling Core is to promote the transition of mainstream Biology to a math-based science.The Core engages researchers in developing appropriate mathematical descriptions for their biological network, and for analyzing their network function using computational simulations or mathematical analysis tools. The Core provides software (including loaded laptops), hands-on training, and holds presentations and workshops to illustrate the utility and strategy of mathematical modeling. One of the missions of the Computational Core of the Center is to maintain computational resources which Center members can use in their projects for modeling and data analysis. SDCSB San Diego Center for Systems Biology Lev Tsimring
Micofluidics The Microscale Cell and Immune Analysis (MICA) platform provides lab-on-a-chip technology for single-cell, real-time analysis of signaling pathways. University of New Mexico New Mexico Spatio Temporal Modeling Center, Albuquerque, New Mexico Anup Singh, Conrad James
MOOSE MOOSE is designed to handle large complex simulations especially in biology. MOOSE spans the range from single molecules to subcellular networks, from single cells to neuronal networks, and to still larger systems. It is backwards-compatible with GENESIS, and forward compatible with Python and XML-based model definition standards like SBML and MorphML. National Center for Biological Sciences, Bhalla Laboratory, India Systems Biology Center New York Upindar Bhalla
Mouse Diversity Genotyping Array The Mouse Diversity Genotyping Array is the most advanced high-density mouse genotyping microarray available. The probe annotation files and the genotypes in the Training Set associated with the array are provided. The Jackson Laboratory Center for Genome Dynamics Imogen Hurley
Mouse Map Converter Mouse Map Converter is a simple web interface for converting mouse genome coordinates between MIT Markers, Base Pair Positions and Centimorgan Positions. The conversion process is based on the mouse map described in “A New Standard Genetic Map for the Laboratory Mouse” by Cox et al. 2009. The Jackson Laboratory Center for Genome Dynamics Imogen Hurley
Mouse Phylogeny Viewer Mouse Phylogeny Viewer is a custom genome browser designed by the Center for Genome Dynamics. It provides the user with reliable and detailed answers to questions on thehaplotype diversity and phylogenetic origin of the genetic variation underlying any genomic region of most laboratory strains (both classical and wild-derived). The Jackson Laboratory Center for Genome Dynamics Imogen Hurley
Multiple trait measurements in 43 inbred mouse strains A phenotypic survey was performed on males and females of 43 inbred strains for body composition (weight, fat, lean tissue mass and bone mineral density), plasma triglycerides, HDL and total cholesterol, glucose, insulin, and leptin levels while mice consumed a high fat, high cholesterol diet. The Jackson Laboratory Center for Genome Dynamics Imogen Hurley
National Short Course on Systems Biology of Morphogenesis and Spatial Dynamics This national short course in Systems Biology explores the themes of Morphogenesis and Spatial Dynamics. The course consists of lectures, wet bench experimentation and hands-on modeling and is designed for graduate students, postdocs and faculty/industry researchers with little or no formal training in systems biology. The course is held at UCI annually each January. Videos/notes of course lectures are available from the website. University of California Irvine Center for Complex Biological Systems Felix Grun
NETWORK BIOINFORMATICS CORE Biomedical research is at a critical juncture in which vast amounts of information on molecules and molecular interactions are being collected, but methods to integrate and analyze these data are still in their infancy. The sheer number and variety of technologies is staggering. For instance, global mRNA profiles are obtained using DNA microarrays or next-generation sequencing, while changes in protein state and metabolite concentrations are quantified with mass spectrometry and other advanced techniques. In terms of molecular interactions, protein-protein binding is measured using yeast-two-hybrid assays or co-affinity purification, while protein-DNA and protein-RNA binding are measured with technologies such as ChIP-Seq or RIP-Chip. There has also been an explosion in techniques for mapping genetic networks, including Synthetic Genetic Arrays (SGA) and Epistatic Miniarray Profile (EMAP), which identify epistatic relationships such as synthetic lethality or suppression.This enormous collection of measurement types necessitates a strong experimental design strategy and bioinformatic framework to integrate and interpret the data in the context of models of networks and pathways. SDCSB San Diego Center for Systems Biology SDCSB Coordinator
Neutral Enhancer Evolutionary Algorithm (NEEA) The following archive contains the C code for implementing the NEEA algorithm. The code uses the transcriptional model to find an ordered set of mutations that can transform enhancer A into enhancer B while maintaining the model-predicted expression pattern constant. NEEA assumes that the enhancers are under stabilizing selection and therefore that enhancer A and enhancer B have similar expression patterns. The set of mutations are derived by calculating the minimum edit distance separating both enhancers and generating a sequence alignment. It is necessary to have a reference or “ideal” pattern necessary for the code to work properly. NEEA code, last updated: October 15, 2012. The University of Chicago Chicago Center for Systems Biology John Reinitz
Particle_Picking imageJ plugins to extract spatial point patterns of nanoparticle distributions on EM images and analyze the patterns for colocalizations and clustering University of New Mexico New Mexico Spatio Temporal Modeling Center, Albuquerque, New Mexico Stanly Steinberg, Michael Wester
Pathway Linker Biomedical research often focuses on altering the functions of selected proteins. These changes can unexpectedly perturb signaling pathways and non-specifically affect several cellular processes. PathwayLinker can assist experimental work by linking the queried proteins to signaling pathways through protein-protein and/or genetic interactions. PathwayLinker identifies and visualizes the first neighbor interactor network of the queried proteins, analyzes the signaling pathway memberships of the proteins in this subnet, and provides links to further online resources. This resource was created by Illes Farkes. UCSF Center for Systems and Synthetic Biology Illes Farkes
PathwayGenerator Automatically generated pathways from receptors to effectors created using the neuronal signalome. Mount Sinai School of Medicine, Ma’ayan Laboratory Systems Biology Center New York Avi Ma’ayan
Plenum Dynamical Grammar Simulator Plenum is a simulation software written in Mathematica for dynamical grammar models. Dynamical grammars are an elegant language for representing complex processes that include stochastic events and continuous dynamics. University of California Irvine Center for Complex Biological Systems Eric Mjolsness
PPARgamma2 gene expression signature in U-33 / gamma2 and U-33/c mouse cell lines Gene expression was examined in murine marrow-derived U-33 cells which represent a clonal cell line spontaneously immortalized in the long term bone marrow culture conditions. The Jackson Laboratory Center for Genome Dynamics Imogen Hurley
Presynaptome Literature-based protein-protein interactions extracted from low-throughput experimental studies reporting interactions in mammalian presynaptic nerve terminals. Mount Sinai School of Medicine, Ma’ayan Laboratory Systems Biology Center New York Avi Ma’ayan
PRIORITY Software Software package for de novo motif discovery. Its goal is to incorporate informative position-based priors into a collapsed Gibbs sampling algorithm. Duke University Center for Systems Biology, Durham, NC Alex Hartemink
PTMfunc Recent advances in mass spectrometry have permitted the identification of thousands of posttranslational modifications (PTMs) including phosphorylation and ubiquitylation. It has been difficult, however, to determine which modifications are biologically meaningful. Center investigators Pedro Beltrao, Nevan Krogan, Al Burlingame, Wendell Lim and colleagues developed a method of prioritizing PTMs, leading to predictors of functional relevance, and identification of regulatory hot spots. UCSF Center for Systems and Synthetic Biology Pedro Beltrao
PTMScout Web application for viewing and analyzing data from mass spectrometry experiments and other datasets for post-translational protein modifications. The goal of PTMScout is to provide a useable interface for biologists to easily work with large datasets of post-translational measurements. Harvard Medical School/ M.I.T. Center for Cell Decision Processes, Boston, MA Kristen Naegle
QuantBio-Tools QuantBio Tools is a framework that provides a pipeline for common data manipulation and analysis tasks. It pieces together several of the individual software resources developed as part of the Center for Quantitative Biology at Princeton. Princeton University Center for Quantitative Biology Mark Schroeder
Quantitative_Imaging The Quantitative Imaging Core provides reagents and instruments for high resolution electron microscopy and super-resolution intravital fluoresence microscopy. University of New Mexico New Mexico Spatio Temporal Modeling Center, Albuquerque, New Mexico Bridget Wilson, Keith Lidke
Scientific Inference Systems Tools A collection of software and packages for modeling and image analysis on systems inferences. University of California Irvine Center for Complex Biological Systems Eric Mjolsness
SERV SERV (Sequence-based Estimation of Repeat Variability) is a web-based algorithm that predicts tandem repeats and their variability for an entered sequence / genome. Harvard FAS Center for Systems Biology Center for Modular Biology Kevin Verstrepen
Sets2Networks Sets2Networks (S2N) is general method for network inference from repeated observations of sets of related entities. Given experimental observations of sets of related entities, S2N infers the underlying network of binary interactions between these entities by generating an ensemble of networks consistent with the data; the frequency of occurrence of a given interaction throughout this ensemble is interpreted as the probability that the interaction is present in the underlying real network. Mount Sinai School of Medicine, Ma’ayan Laboratory Systems Biology Center New York Avi Ma’ayan
Sig2BioPAX Sig2BioPAX is a comand-line Java program that can be used to convert structured text files describing molecular interactions into the BioPAX Level 3 standard format Mount Sinai School of Medicine, Ma’ayan Laboratory Systems Biology Center New York Avi Ma’ayan
Sigmoid The SIGMOID project is intended to produce a database of cellular signaling pathways and models thereof, to marshall the major forms of data and knowledge required as input to cellular modeling software and also to organize the outputs. University of California Irvine Center for Complex Biological Systems Eric Mjolsness
SiteSleuth SiteSleuth is a tool for identifying transcription factor binding sites based on physicochemical features of the DNA. It is described in Maienschein-Cline,M., Dinner, A. R., Hlavacek, W. S. & Mu, F. Improved predictions of transcription factor binding sites using physicochemical features of DNA. Nuc. Acid. Res., Advance Access (2012). PMID: 22923524 PMCID: PMC3526315 The University of Chicago Chicago Center for Systems Biology Aaron Dinner
SMLR: Sparse Multinomial Logistic Regression Software package for sparse classification, based on the well-studied multinomial logistic regression framework with a Bayesian perspective. Duke University Center for Systems Biology, Durham, NC Alex Hartemink
SNAVI SNAVI (Signaling Networks Analysis and Visualization) is Windows-based desktop application that implements standard network analysis methods to compute the clustering, connectivity distribution, and detection of network motifs, as well as provides means to visualize networks and network motifs. Mount Sinai School of Medicine, Ma’ayan Laboratory Systems Biology Center New York Avi Ma’ayan
SNPtools SNPtools is an R package that selects SNPs from a set of inbred strains. The SNPs are a combination of the Sanger SNPs and a set of SNPs imputed onto 88 laboratory inbred strains by UNC. The software queries the SNP files and quickly returns SNPs for the requested strains in the region of interest. It then allows the user to plot these SNPs, intersect them with genes and classify them. The SNP files are zipped and indexed using Tabix. The gene locations are derived from the Mouse Genome Informatics gene feature file. The Jackson Laboratory Center for Genome Dynamics Imogen Hurley
Stiff Reaction Diffusion Solvers Fast Numerical Algorithms for Stiff Reaction-Diffusion Equations. Provdies Matlab and C codes based on a novel and efficient algorithm for Reaction-Diffusion equations that model spatial dynamics of complex biological systems. The numerical method used in the code is designed for effective treatment of stiff reactions in spatial systems. University of California Center for Complex Biological Systems Qing Nie
Systems Biology Seminar Series A monthly seminar series for CCBS-affiliated scientists with interests in Systems Biology. The seminars are presented by a mix of local and outside speakers. University of California Irvine Center for Complex Biological Systems Karen Martin
Transcription regulatory model The following archive contains the source code that implements the transcriptional regulatory model. The code optimizes the model parameters by using Lam simulated annealing to minimize the sum of the squared differences between the observed and predicted expression patterns of a set of gene regulatory sequences. The archive contains tools for calculating the model rms as well as for analyzing the effects of individual transcriptional regulatory mechanisms. This implementation of the transcription model is capable of predicting expression patterns directly from sequence. In addition, it can be used to generate synthetic sequences that match a given expression pattern as closely as possible. The University of Chicago Chicago Center for Systems Biology John Reinitz
TreeQA TreeQA TreeQA is a quantitative genome wide association mapping algorithm. TreeQA utilizes local perfect phylogenies constructed in genomic regions exhibiting no evidence of historical recombination. By efficient algorithm design and implementation, TreeQA can efficiently conduct quantitative genome-wide association analysis and is more effective than the previous methods. The Jackson Laboratory Center for Genome Dynamics Imogen Hurley
u-track MATLAB software package for high density multiple particle tracking. Harvard Medical School Center for Cell Decision Processes, Boston, MA Khuloud Jaqaman
Uncovering Genes and Regulatory Pathways Related to Urinary Albumin Excretion in Mice In the first study (Hageman et al. J Am Soc Nephrol. 2011), we mapped three significant and one suggestive QTL on Chromosomes (Chrs) 1, 4, 15, and 17, respectively, for increased albumin excretion (measured as albumin-to-creatinine ratio) in a cross between the MRL/MpJ and SM/J mouse inbred strains. By combining data from several sources and by utilizing gene expression data, we identified Tlr12 as a likely candidate for the Chr 4 QTL. Through the mapping of 33,881 transcripts measured by microarray on kidney RNA from each of the 173 male F2 animals, we identified several downstream pathways associated with these QTL. Among these were the glycan degradation, leukocyte migration, and antigen presenting pathways. We demonstrate that by combining data from multiple sources, we can identify not only genes that are likely to be causal candidates for QTL, but also the pathways through which these genes act to alter phenotypes. This combined approach provides valuable insights into the causes and consequences of renal disease. Female MRL/MpJ (MRL) mice were crossed with male SM/J (SM) mice; their progeny were intercrossed to produce 371 F2 animals. Only 173 F2 males were used for this study.In the second study (Hageman et al. Genetics 2011), we proposed a Bayesian statistical method to infer networks of causal relationships among genotypes and phenotypes using expression quantitative trait loci (eQTL) data from genetically randomized populations. Causal relationships between network variables are described with hierarchical regression models. Prior distributions on the network structure enforce graph sparsity and have the potential to encode prior biological knowledge about the network. An efficient Monte Carlo method is used to search across the model space and sample highly probable networks. The result is an ensemble of networks that provide a measure of confidence in the estimated network topology. These networks can be used to make predictions of system-wide response to perturbations. We applied our method to kidney gene expression data from the MRL/MpJ × SM/J intercross population and predicted a previously uncharacterized feedback loop in the local renin-angiotensin system. The Jackson Laboratory Center for Genome Dynamics Imogen Hurley