TMPDB: a database of experimentally-characterized transmembrane topologies

TMPDB is a database of experimentally-characterized transmembrane (TM) topologies. TMPDB release 6.2 contains a total of 302 TM protein sequences, in which 276 are alpha-helical sequences, 17 beta-stranded, and 9 alpha-helical sequences with short pore-forming helices buried in the membrane. The TM topologies in TMPDB were determined experimentally by means of X-ray crystallography, NMR, gene fusion technique, substituted cysteine accessibility method, N-linked glycosylation experiment and other biochemical methods. TMPDB would be useful as a test and/or training dataset in improving the proposed TM topology prediction methods or developing novel methods with higher performance, and as a guide for both the bioinformaticians and biologists to better understand TM proteins. TMPDB and its subsets are freely available at the following web site: http://bioinfo.si.hirosaki-u.ac.jp/~TMPDB/.     

BioPAX support in CellDesigner

MOTIVATION: BioPAX is a standard language for representing and exchanging models of biological processes at the molecular and cellular levels. It is widely used by different pathway databases and genomics data analysis software. Currently, the primary source of BioPAX data is direct exports from the curated pathway databases. It is still uncommon for wet-lab biologists to share and exchange pathway knowledge using BioPAX. Instead, pathways are usually represented as informal diagrams in the literature. In order to encourage formal representation of pathways, we describe a software package that allows users to create pathway diagrams using CellDesigner, a user-friendly graphical pathway-editing tool and save the pathway data in BioPAX Level 3 format. AVAILABILITY: The plug-in is freely available and can be downloaded at ftp://ftp.pantherdb.org/CellDesigner/plugins/BioPAX/ CONTACT: huaiyumi@usc.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

ARDesigner: a web-based system for allosteric RNA design

RNA molecules play vital informational, structural, and functional roles in molecular biology, making them ideal targets for synthetic biology. However, several challenges remain for engineering novel allosteric RNA molecules, and the development of efficient computational design techniques is vitally needed. Here we describe the development of Allosteric RNA Designer (ARDesigner), a user-friendly and freely available web-based system for allosteric RNA design that incorporates mutational robustness in the design process. The system output includes detailed design information in a graphical HTML format. We used ARDesigner to engineer a temperature-sensitive AR, and found that the resulting design satisfied the prescribed properties/input. ARDesigner provides a simple means for researchers to design allosteric RNAs with specific properties. With its versatile framework and possibilities for further enhancement, ARDesigner may serve as a useful tool for synthetic biologists and therapeutic design. ARDesigner and its executable version are freely available at http://biotech.bmi.ac.cn/ARDesigner.     

OligoMatcher

OligoMatcher is a web-based tool for analysis and selection of unique oligonucleotide sequences for gene silencing by antisense oligonucleotides (ASOs) or small interfering RNA (siRNA). A specific BLAST server was built for analysing sequences of ASOs that target pre-mRNA in the cell nucleus. Tissue- and cell-specific expression data of potential cross-reactive genes are integrated in the OligoMatcher program, which allows biologists to select unique oligonucleotide sequences for their target genes in specific experimental systems. AVAILABILITY: The OligoMatcher web server is available at http://shelob.cs.iupui.edu:18081/oligomatch.php. The source code is freely available for non-profit use on request to the authors. CONTACT: Mathew Palakal (mpalakal@cs.iupui.edu) or Shuyu Li (li_shuyu_dan@lilly.com).     

Design patterns for wildlife‐related camera trap image analysis

This paper describes and explains design patterns for software that supports how analysts can efficiently inspect and classify camera trap images for wildlife‐related ecological attributes. Broadly speaking, a design pattern identifies a commonly occurring problem and a general reusable design approach to solve that problem. A developer can then use that design approach to create a specific software solution appropriate to the particular situation under consideration. In particular, design patterns for camera trap image analysis by wildlife biologists address solutions to commonly occurring problems they face while inspecting a large number of images and entering ecological data describing image attributes. We developed design patterns for image classification based on our understanding of biologists' needs that we acquired over 8 years during development and application of the freely available Timelapse image analysis system. For each design pattern presented, we describe the problem, a design approach that solves that problem, and a concrete example of how Timelapse addresses the design pattern. Our design patterns offer both general and specific solutions related to: maintaining data consistency, efficiencies in image inspection, methods for navigating between images, efficiencies in data entry including highly repetitious data entry, and sorting and filtering image into sequences, episodes, and subsets. These design patterns can inform the design of other camera trap systems and can help biologists assess how competing software products address their project‐specific needs along with determining an efficient workflow.     

Structure prediction meta server

SUMMARY: The Structure Prediction Meta Server offers a convenient way for biologists to utilize various high quality structure prediction servers available worldwide. The meta server translates the results obtained from remote services into uniform format, which are consequently used to request a jury prediction from a remote consensus server Pcons. AVAILABILITY: The structure prediction meta server is freely available at http://BioInfo.PL/meta/, some remote servers have however restrictions for non-academic users, which are respected by the meta server. SUPPLEMENTARY INFORMATION: Results of several sessions of the CAFASP and LiveBench programs for assessment of performance of fold-recognition servers carried out via the meta server are available at http://BioInfo.PL/services.html.     

Phylogenetic mixtures on a single tree can mimic a tree of another topology

Phylogenetic mixtures model the inhomogeneous molecular evolution commonly observed in data. The performance of phylogenetic reconstruction methods where the underlying data are generated by a mixture model has stimulated considerable recent debate. Much of the controversy stems from simulations of mixture model data on a given tree topology for which reconstruction algorithms output a tree of a different topology; these findings were held up to show the shortcomings of particular tree reconstruction methods. In so doing, the underlying assumption was that mixture model data on one topology can be distinguished from data evolved on an unmixed tree of another topology given enough data and the "correct" method. Here we show that this assumption can be false. For biologists, our results imply that, for example, the combined data from two genes whose phylogenetic trees differ only in terms of branch lengths can perfectly fit a tree of a different topology.     

FaBox: an online toolbox for fasta sequences

FaBox is a collection of simple and intuitive web services that enable biologists and medical researchers to quickly perform typical task with sequence data. The services makes it easy to extract, edit, and replace sequence headers and join or divide data sets based on header information. Other services include collapsing a set of sequences into haplotypes and automated formatting of input files for a number of population genetics programs, such as arlequin , tcs and mrbayes . The toolbox is expected to grow on the basis of requests for particular services and converters in the future. FaBox is freely available at http://www.birc.au.dk/fabox .     

Profiling small RNA reveals multimodal substructural signals in a Boltzmann ensemble

As the biomedical impact of small RNAs grows, so does the need to understand competing structural alternatives for regions of functional interest. Suboptimal structure analysis provides significantly more RNA base pairing information than a single minimum free energy prediction. Yet computational enhancements like Boltzmann sampling have not been fully adopted by experimentalists since identifying meaningful patterns in this data can be challenging. Profiling is a novel approach to mining RNA suboptimal structure data which makes the power of ensemble-based analysis accessible in a stable and reliable way. Balancing abstraction and specificity, profiling identifies significant combinations of base pairs which dominate low-energy RNA secondary structures. By design, critical similarities and differences are highlighted, yielding crucial information for molecular biologists. The code is freely available via http://gtfold.sourceforge.net/profiling.html.     

T(E)Xtopo: shaded membrane protein topology plots in LAT(E)X2epsilon

SUMMARY: T(E)Xtopo is a LAT(E)X2epsilon macro package for plotting topology data directly from PHD predictions or SwissProt database files in publication-ready quality. The plot can be shaded automatically to emphasize conserved residues or functional properties of the residue sidechains. The addition of rich decorations, such as labels, annotations and legends, is easily accomplished. AVAILABILITY: The T(E)Xtopo macro package and a full on-line documentation are freely available at http://homepages.uni-tuebingen.de/beitz/ CONTACT: eric.beitz@uni-tuebingen.de     

Protein homologous cores and loops: important clues to evolutionary relationships between structurally similar proteins

Background  

To discover remote evolutionary relationships and functional similarities between proteins, biologists rely on comparative sequence analysis, and when structures are available, on structural alignments and various measures of structural similarity. The measures/scores that have most commonly been used for this purpose include: alignment length, percent sequence identity, superposition RMSD and their different combinations. More recently, we have introduced the "Homologous core structure overlap score" (HCS) and the "Loop Hausdorff Measure" (LHM). Along with these we also consider the "gapped structural alignment score" (GSAS), which was introduced earlier by other researchers.     

cBrother: relaxing parental tree assumptions for Bayesian recombination detection

Bayesian multiple change-point models accurately detect recombination in molecular sequence data. Previous Java-based implementations assume a fixed topology for the representative parental data. cBrother is a novel C language implementation that capitalizes on reduced computational time to relax the fixed tree assumption. We show that cBrother is 19 times faster than its predecessor and the fixed tree assumption can influence estimates of recombination in a medically-relevant dataset. Availability: cBrother can be freely downloaded from http://www.biomath.org/dormanks/ and can be compiled on Linux, Macintosh and Windows operating systems. Online documentation and a tutorial are also available at the site.     

Predicting coaxial helical stacking in RNA junctions

RNA junctions are important structural elements that form when three or more helices come together in space in the tertiary structures of RNA molecules. Determining their structural configuration is important for predicting RNA 3D structure. We introduce a computational method to predict, at the secondary structure level, the coaxial helical stacking arrangement in junctions, as well as classify the junction topology. Our approach uses a data mining approach known as random forests, which relies on a set of decision trees trained using length, sequence and other variables specified for any given junction. The resulting protocol predicts coaxial stacking within three- and four-way junctions with an accuracy of 81% and 77%, respectively; the accuracy increases to 83% and 87%, respectively, when knowledge from the junction family type is included. Coaxial stacking predictions for the five to ten-way junctions are less accurate (60%) due to sparse data available for training. Additionally, our application predicts the junction family with an accuracy of 85% for three-way junctions and 74% for four-way junctions. Comparisons with other methods, as well applications to unsolved RNAs, are also presented. The web server Junction-Explorer to predict junction topologies is freely available at: http://bioinformatics.njit.edu/junction.     

MedlineR: an open source library in R for Medline literature data mining

SUMMARY: We describe an open source library written in the R programming language for Medline literature data mining. This MedlineR library includes programs to query Medline through the NCBI PubMed database; to construct the co-occurrence matrix; and to visualize the network topology of query terms. The open source nature of this library allows users to extend it freely in the statistical programming language of R. To demonstrate its utility, we have built an application to analyze term-association by using only 10 lines of code. We provide MedlineR as a library foundation for bioinformaticians and statisticians to build more sophisticated literature data mining applications. AVAILABILITY: The library is available from http://dbsr.duke.edu/pub/MedlineR.     

The HMMTOP transmembrane topology prediction server

The HMMTOP transmembrane topology prediction server predicts both the localization of helical transmembrane segments and the topology of transmembrane proteins. Recently, several improvements have been introduced to the original method. Now, the user is allowed to submit additional information about segment localization to enhance the prediction power. This option improves the prediction accuracy as well as helps the interpretation of experimental results, i.e. in epitope insertion experiments. Availability: HMMTOP 2.0 is freely available to non-commercial users at http://www.enzim.hu/hmmtop. Source code is also available upon request to academic users.     

NetSeed: a network-based reverse-ecology tool for calculating the metabolic interface of an organism with its environment

NetSeed is a web tool and Perl module for analyzing the topology of metabolic networks and calculating the set of exogenously acquired compounds. NetSeed is based on the seed detection algorithm, developed and validated in previous studies. AVAILABILITY: The NetSeed web-based tool, open-source Perl module, examples and documentation are freely available online at: http://depts.washington.edu/elbogs/NetSeed.