In silico Biochemical Reaction Network Analysis (IBRENA): a package for simulation and analysis of reaction networks

Summary: We present In silico Biochemical Reaction Network Analysis(IBRENA), a software package which facilitates multiple functionsincluding cellular reaction network simulation and sensitivityanalysis (both forward and adjoint methods), coupled with principalcomponent analysis, singular-value decomposition and model reduction.The software features a graphical user interface that aids simulationand plotting of in silico results. While the primary focus isto aid formulation, testing and reduction of theoretical biochemicalreaction networks, the program can also be used for analysisof high-throughput genomic and proteomic data. Availability: The software package, manual and examples areavailable at http://www.eng.buffalo.edu/~neel/ibrena Contact: neel{at}eng.buffalo.edu Associate Editor: Limsoon Wong     

A simple and efficient algorithm for gene selection using sparse logistic regression

MOTIVATION: This paper gives a new and efficient algorithm for the sparse logistic regression problem. The proposed algorithm is based on the Gauss-Seidel method and is asymptotically convergent. It is simple and extremely easy to implement; it neither uses any sophisticated mathematical programming software nor needs any matrix operations. It can be applied to a variety of real-world problems like identifying marker genes and building a classifier in the context of cancer diagnosis using microarray data. RESULTS: The gene selection method suggested in this paper is demonstrated on two real-world data sets and the results were found to be consistent with the literature. AVAILABILITY: The implementation of this algorithm is available at the site http://guppy.mpe.nus.edu.sg/~mpessk/SparseLOGREG.shtml Supplementary Information: Supplementary material is available at the site http://guppy.mpe.nus.edu.sg/~mpessk/SparseLOGREG.shtml     

LabArray: real-time imaging and analytical tool for microarrays

SUMMARY: Microarrays have been used to perform high-throughput genetic analyses such as single-nucleotide polymorphisms detection and microbial genome analysis. Some of these analyses require real-time monitoring of the hybridization signals with respect to a varying experimental condition, such as temperature. However, current microarray imaging and analysis packages typically do not possess such real-time capabilities. Therefore, microarray image analyses are often time-consuming and labour-intensive. LabArray was developed to expedite such processes by enabling real-time monitoring of microarray signals. AVAILABILITY: LabArray is available at http://www.eng.nus.edu.sg/civil/Labarray/labarray.htm CONTACT: cveliuwt@nus.edu.sg SUPPLEMENTARY INFORMATION: Screenshots and instructions for use are available at the above website.     

GENOME: a rapid coalescent-based whole genome simulator

Summary: GENOME proposes a rapid coalescent-based approach tosimulate whole genome data. In addition to features of standardcoalescent simulators, the program allows for recombinationrates to vary along the genome and for flexible population histories.Within small regions, we have evaluated samples simulated byGENOME to verify that GENOME provides the expected LD patternsand frequency spectra. The program can be used to study thesampling properties of any statistic for a whole genome study. Availability: The program and C++ source code are availableonline at http://www.sph.umich.edu/csg/liang/genome/ Contact: lianglim{at}umich.edu Supplementary information: Supplementary data are availableat Bioinformatics online. Associate Editor: Martin Bishop     

DeconMSn: a software tool for accurate parent ion monoisotopic mass determination for tandem mass spectra

Summary: DeconMSn accurately determines the monoisotopic massand charge state of parent ions from high-resolution tandemmass spectrometry data, offering significant improvement forLTQ_FT and LTQ_Orbitrap instruments over the commercially deliveredThermo Fisher Scientific's extract_msn tool. Optimal parention mass tolerance values can be determined using accurate massinformation, thus improving peptide identifications for high-massmeasurement accuracy experiments. For low-resolution data fromLCQ and LTQ instruments, DeconMSn incorporates a support-vector-machine-basedcharge detection algorithm that identifies the most likely chargeof a parent species through peak characteristics of its fragmentationpattern. Availability: http://ncrr.pnl.gov/software/ or http://www.proteomicsresource.org/ Contact: rds{at}pnl.gov Supplementary information: PowerPoint presentation/Poster onhttp://ncrr.pnl.gov/software/. Associate Editor: Alfonso Valencia     

PedMine--a simulated annealing algorithm to identify maximally unrelated individuals in population isolates

Summary: In family-based genetic studies, it is often usefulto identify a subset of unrelated individuals. When such studiesare conducted in population isolates, however, most if not allindividuals are often detectably related to each other. To identifya set of maximally unrelated (or equivalently, minimally related)individuals, we have implemented simulated annealing, a general-purposealgorithm for solving difficult combinatorial optimization problems.We illustrate our method on data from a genetic study in theOld Order Amish of Lancaster County, Pennsylvania, a populationisolate derived from a modest number of founders. Given oneor more pedigrees, our program automatically and rapidly extractsa fixed number of maximally unrelated individuals. Availability: http://www.hg.med.umich.edu/labs/douglaslab/software.html(version 1.0.0) Contact: jddoug{at}umich.edu Associate Editor: Martin Bishop     

A precise and scalable method for querying genes in chromosomal banding regions based on cytogenetic annotations

Motivation: Staining the human metaphase chromosomes revealscharacteristic banding patterns known as cytogenetic bands orcytobands. Using technologies based on metaphase chromosomes,researchers have accumulated much knowledge about the correlationsbetween human diseases and specific cytoband aberrations, indicatingthe presence of disease-associated genes in those bands. Withthe progress of human genome project and techniques such asfluorescent in situ hybridization, many genes have been assignedto the cytobands and annotated in public databases, making itpossible to find all genes in the disease-related cytobandsthrough database queries. However, finding genes in cytobandsremains an imprecise process, partly due to the insufficiencyof current methods for cytoband queries, especially for thosebased on cytogenetic annotations. Results: By transforming the cytoband annotations into numericalsegments, a new query method is developed that is able to accuratelydefine any cytogenetic ranges in human chromosomes. A querysystem (designated cytoband query sys CQS) is implemented usingcytogenetic annotations in the public domain. Judged by a performancetest, CQS executed as accurately as expected using cytogeneticannotations from NCBI Map Viewer. The new method is scalableand can be applied to genomes from other species. Availability: The CQS is freely accessible over the Internetat http://moris.csie.ncku.edu.tw/cqs/ Contact: clh9{at}mail.ncku.edu.tw Supplementary information: http://moris.csie.ncku.edu.tw/cqs/     

SEGE: A database on 'intron less/single exonic' genes from eukaryotes

SUMMARY: Eukaryotes have both 'intron containing' and 'intron less' genes. Several databases are available for 'intron containing' genes in eukaryotes. In this note, we describe a database for 'intron less' genes from eukaryotes. 'Intron less' eukaryotic genes having prokaryotic architecture will help to understand gene evolution in a much simpler way unlike 'intron containing' genes. AVAILABILITY: SEGE is available at http://intron.bic.nus.edu.sg/seg/ CONTACT: mmeena@ntu.edu.sg     

Web Watch

Plant biology - with an emphasis on photosynthesis

The Great Plant Escape http://www.urbanext.uiuc.edu/gpe/gpe.html

The Power of Green.http://researchmag.asu.edu/stories/power.html

Photosynthesis http://biology.ck.uc.edu/courses/biol04/photosyn.htm

An Introduction to Photosynthesis and its Applicationhttp://photoscience.la.asu.edu/photosyn/education/photointro.html

Aliens Explorers - Photosynthesis http://www.alienexplorer.com/ecology/topic3.html

The Photosynthesis Processhttp://www.ifmt.nf.ca/mi-net/enviro/photo3.htm     

ROBIN: a tool for genome rearrangement of block-interchanges

Summary: ROBIN is a web server for analyzing genome rearrangementof block-interchanges between two chromosomal genomes. It takestwo or more linear/circular chromosomes as its input, and computesthe number of minimum block-interchange rearrangements betweenany two input chromosomes for transforming one chromosome intoanother and also determines an optimal scenario taking thisnumber of rearrangements. The input can be either bacterial-sizesequence data or landmark-order data. If the input is sequencedata, ROBIN will automatically search for the identical landmarksthat are the homologous/conserved regions shared by all theinput sequences. Availability: ROBIN is freely accessed at http://genome.life.nctu.edu.tw/ROBIN Contact: cllu{at}mail.nctu.edu.tw     

BLISS 2.0: a web-based tool for predicting conserved regulatory modules in distantly-related orthologous sequences

Summary: BLISS 2.0 is a web-based application for identifyingconserved regulatory modules in distantly related orthologoussequences. Unlike existing approaches, it performs the cross-genomecomparison at the binding site level. Experimental results onsimulated and real world data indicate that BLISS 2.0 can identifyconserved regulatory modules from sequences with little overallsimilarity at the DNA sequence level. Availability: http://www.blisstool.org/ Contact: leizhou{at}ufl.edu Associate Editor: Olga Troyanskaya     

EPIMHC: a curated database of MHC-binding peptides for customized computational vaccinology

Summary: EPIMHC is a relational database of MHC-binding peptidesand T cell epitopes that are observed in real proteins. Currently,the database contains 4867 distinct peptide sequences from varioussources, including 84 tumor-associated antigens. The EPIMHCdatabase is accessible through a web server that has been designedto facilitate research in computational vaccinology. Importantly,peptides resulting from a query can be selected to derive specificmotif-matrices. Subsequently, these motif-matrices can be usedin combination with a dynamic algorithm for predicting MHC-bindingpeptides from user-provided protein queries. Availability: The EPIMHC database server is hosted by the Dana-FarberCancer Institute at the site http://immunax.dfci.harvard.edu/bioinformatics/epimhc/ Contact: reche{at}research.dfci.harvard.edu     

AIMIE: a web-based environment for detection and interpretation of significant sequence motifs in prokaryotic genomes

Motivation: Genomes contain biologically significant informationthat extends beyond that encoded in genes. Some of this informationrelates to various short dispersed repeats distributed throughoutthe genome. The goal of this work was to combine tools for detectionof statistically significant dispersed repeats in DNA sequenceswith tools to aid development of hypotheses regarding theirpossible physiological functions in an easy-to-use web-basedenvironment. Results: Ab Initio Motif Identification Environment (AIMIE)was designed to facilitate investigations of dispersed sequencemotifs in prokaryotic genomes. We used AIMIE to analyze theEscherichia coli and Haemophilus influenzae genomes in orderto demonstrate the utility of the new environment. AIMIE detectedrepeated extragenic palindrome (REP) elements, CRISPR repeats,uptake signal sequences, intergenic dyad sequences and severalother over-represented sequence motifs. Distributional patternsof these motifs were analyzed using the tools included in AIMIE. Availability: AIMIE and the related software can be accessedat our web site http://www.cmbl.uga.edu/software.html. Contact: mrazek{at}uga.edu Associate Editor: Alex Bateman     

MetaboNexus: an interactive platform for integrated metabolomics analysis

MetaboNexus is an interactive metabolomics data analysis platform that integrates pre-processing of raw peak data with in-depth statistical analysis and metabolite identity search. It is designed to work as a desktop application hence uploading large files to web servers is not required. This could speed up the data analysis process because server queries or queues are avoided, while ensuring security of confidential clinical data on a local computer. With MetaboNexus, users can progressively start from data pre-processing, multi- and univariate analysis to metabolite identity search of significant molecular features, thereby seamlessly integrating critical steps for metabolite biomarker discovery. Data exploration can be first performed using principal components analysis, while prediction and variable importance can be calculated using partial least squares-discriminant analysis and Random Forest. After identifying putative features from multi- and univariate analyses (e.g. t test, ANOVA, Mann–Whitney U test and Kruskal–Wallis test), users can seamlessly determine the molecular identity of these putative features. To assist users in data interpretation, MetaboNexus also automatically generates graphical outputs, such as score plots, diagnostic plots, boxplots, receiver operating characteristic plots and heatmaps. The metabolite search function will match the mass spectrometric peak data to three major metabolite repositories, namely HMDB, MassBank and METLIN, using a comprehensive range of molecular adducts. Biological pathways can also be searched within MetaboNexus. MetaboNexus is available with installation guide and tutorial at http://www.sph.nus.edu.sg/index.php/research-services/research-centres/ceohr/metabonexus, and is meant for the Windows Operating System, XP and onwards (preferably on 64-bit). In summary, MetaboNexus is a desktop-based platform that seamlessly integrates the entire data analytical workflow and further provides the putative identities of mass spectrometric data peaks by matching them to databases.     

Align human interactome with phenome to identify causative genes and networks underlying disease families

Motivation: Understanding the complexity in gene–phenotyperelationship is vital for revealing the genetic basis of commondiseases. Recent studies on the basis of human interactome andphenome not only uncovers prevalent phenotypic overlap and geneticoverlap between diseases, but also reveals a modular organizationof the genetic landscape of human diseases, providing new opportunitiesto reduce the complexity in dissecting the gene–phenotypeassociation. Results: We provide systematic and quantitative evidence thatphenotypic overlap implies genetic overlap. With these results,we perform the first heterogeneous alignment of human interactomeand phenome via a network alignment technique and identify 39disease families with corresponding causative gene networks.Finally, we propose AlignPI, an alignment-based framework topredict disease genes, and identify plausible candidates for70 diseases. Our method scales well to the whole genome, asdemonstrated by prioritizing 6154 genes across 37 chromosomeregions for Crohn's disease (CD). Results are consistent witha recent meta-analysis of genome-wide association studies forCD. Availability: Bi-modules and disease gene predictions are freelyavailable at the URL http://bioinfo.au.tsinghua.edu.cn/alignpi/ Contact: ruijiang{at}tsinghua.edu.cn Supplementary information: Supplementary data are availableat Bioinformatics online. Associate Editor: Trey Ideker     

Tree-guided Bayesian inference of population structures

Motivation: Inferring population structures using genetic datasampled from a group of individuals is a challenging task. Manymethods either consider a fixed population number or ignorethe correlation between populations. As a result, they can losesensitivity and specificity in detecting subtle stratifications.In addition, when a large number of genetic markers are used,many existing algorithms perform rather inefficiently. Result: We propose a new Bayesian method to infer populationstructures using multiple unlinked single nucleotide polymorphisms(SNPs). Our approach explicitly considers the population correlationthrough a tree hierarchy, and treat the population number asa random variable. Using both simulated and real datasets ofworldwide samples, we demonstrate that an incorporated treecan consistently improve the power in detecting subtle populationstratifications. A tree-based model often involves a large numberof unknown parameters, and the corresponding estimation procedurecan be highly inefficient. We further implement a partitionmethod to analytically integrate out all nuisance parametersin the tree. As a result, our method can analyze large SNP datasetswith significantly improved convergence rate. Availability: http://www.stat.psu.edu/~yuzhang/tips.tar Contact: yuzhang{at}stat.psu.edu Supplementary information: Supplementary data are availableat Bioinformatics online. Associate Editor: Keith Crandall