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PubMed2005

Friend, an integrated analytical front-end application for bioinformatics.

UNLABELLED: Friend is a bioinformatics application designed for simultaneous analysis and visualization of multiple structures and sequences of proteins and/or DNA/RNA. The application provides basic functionalities, such as structure visualization, with different rendering and coloring, sequence alignment and simple phylogeny analysis, along with a number of extended features to perform more complex analyses of sequence structure relationships, including structural alignment of proteins, investigation of specific interaction motifs, studies of protein-protein and protein-DNA interactions and protein super-families. It is also useful for functional annotation of proteins, protein modeling and protein folding studies. Friend provides three levels of usage: (1) an extensive GUI for a scientist with no programming experience, (2) a command line interface for scripting for a scientist with some programming experience and (3) the ability to extend Friend with user written libraries for an experienced programmer. The application is linked and communicates with local and remote sequence and structure databases. AVAILABILITY: http://mozart.bio.neu.edu/friend.

Computational Biology↗
PubMed2004

Globally distributed object identification for biological knowledgebases.

The World-Wide Web provides a globally distributed communication framework that is essential for almost all scientific collaboration, including bioinformatics. However, several limits and inadequacies have become apparent, one of which is the inability to programmatically identify locally named objects that may be widely distributed over the network. This shortcoming limits our ability to integrate multiple knowledgebases, each of which gives partial information of a shared domain, as is commonly seen in bioinformatics. The Life Science Identifier (LSID) and LSID Resolution System (LSRS) provide simple and elegant solutions to this problem, based on the extension of existing internet technologies. LSID and LSRS are consistent with next-generation semantic web and semantic grid approaches. This article describes the syntax, operations, infrastructure compatibility considerations, use cases and potential future applications of LSID and LSRS. We see the adoption of these methods as important steps toward simpler, more elegant and more reliable integration of the world's biological knowledgebases, and as facilitating stronger global collaboration in biology.

Animals↗
PubMed2004

BioLingua: a programmable knowledge environment for biologists.

UNLABELLED: BioLingua is an interactive, web-based programming environment that enables biologists to analyze biological systems by combining knowledge and data through direct end-user programming. BioLingua embeds a mature symbolic programming language in a frame-based knowledge environment, integrating genomic and pathway knowledge about a class of similar organisms. The BioLingua language provides interfaces to numerous state-of-the-art bioinformatic tools, making these available as an integrated package through the novel use of web-based programmability and an integrated Wiki-based community code and data store. The pilot instantiation of BioLingua, which has been developed in collaboration with several cyanobacteriologists, integrates knowledge about a subset of cyanobacteria with the Gene Ontology, KEGG and BioCyc knowledge bases. We introduce the BioLingua concept, architecture and language, and give several examples of its use in complex analyses. AVAILABILITY: Extensive documentation is available online at http://nostoc.stanford.edu/Docs/index.html CONTACT: JShrager@Stanford.edu

Artificial Intelligence↗
PubMed2002

Global computing for bioinformatics.

Global computing, the collaboration of idle PCs via the Internet in a SETI@home style, emerges as a new way of massive parallel multiprocessing with potentially enormous CPU power. Its relations to the broader, fast-moving field of Grid computing are discussed without attempting a review of the latter. This review (i) includes a short table of milestones in global computing history, (ii) lists opportunities global computing offers for bioinformatics, (iii) describes the structure of problems well suited for such an approach, (iv) analyses the anatomy of successful projects and (v) points to existing software frameworks. Finally, an evaluation of the various costs shows that global computing indeed has merit, if the problem to be solved is already coded appropriately and a suitable global computing framework can be found. Then, either significant amounts of computing power can be recruited from the general public, or--if employed in an enterprise-wide Intranet for security reasons--idle desktop PCs can substitute for an expensive dedicated cluster.

Computational Biology↗
PubMed2004

Data mining in bioinformatics using Weka.

UNLABELLED: The Weka machine learning workbench provides a general-purpose environment for automatic classification, regression, clustering and feature selection-common data mining problems in bioinformatics research. It contains an extensive collection of machine learning algorithms and data pre-processing methods complemented by graphical user interfaces for data exploration and the experimental comparison of different machine learning techniques on the same problem. Weka can process data given in the form of a single relational table. Its main objectives are to (a) assist users in extracting useful information from data and (b) enable them to easily identify a suitable algorithm for generating an accurate predictive model from it. AVAILABILITY: http://www.cs.waikato.ac.nz/ml/weka.

Algorithms↗
PubMed2002

Experimental and bioinformatics comparison of gene expression between T cells from TIL of liver cancer and T cells from UniGene.

BACKGROUND: The major difficulty of mapping parallel gene expression obtained from solid tumors is mainly due to contaminating cells. In this study, by applying a strategy of parallel gene expression at a cell-cluster or colony level, we have identified the gene expression pattern of T cells within tumor-infiltrating lymphocytes (TJLs) obtained from two liver cancer patients. METHODS: Here a new method was utilized to analyze the parallel gene expression. By using bioinformatics analysis, the data were also compared with T-cell gene expression present in UniGene. RESULTS: Our results demonstrated that 18 genes in specimen A and 13 genes in specimen B were highly expressed after the removal of a nonspecific TIL cDNA library, by pairing gene hybridization; the genes were expressed in CD3+ cells from peripheral blood mononuclear cells (PBMC). By using BlastN search, 17 of the 18, and 12 of the 13 sequences were exhibited, respectively, in Homo sapiens, with a range of BlastN E values of 0 to 4 x 10(-13). The LocusLink distribution in chromosomes obtained from both specimens was not significantly different; 17 of 19 putative genes (both specimen A and specimen B) were observed in the UniGene cluster in Homo sapiens, except for dihydropyrimidinase-related protein-3 and diacyglycerol kinase alpha. Interestingly, only 4 of 19 (21%) putative genes were displayed in the T-cell UniGene database (i.e., LD-78 in Hs. 73817, IL-8 in Hs. 624, TRAIL in Hs. 83429, and Fas ligand in Hs. 2007). CONCLUSIONS: By comparison with the reported data and UniGene, the parallel gene expression of T cells obtained from TIL can provide essential new insights into T-cell activity, T-cell extravasation into tumor tissues, and T-cell cytotoxicity against tumor cells.

Adult↗
PubMed2006

Advanced techniques in placental biology -- workshop report.

Major advances in placental biology have been realized as new technologies have been developed and existing methods have been refined in many areas of biological research. Classical anatomy and whole-organ physiology tools once used to analyze placental structure and function have been supplanted by more sophisticated techniques adapted from molecular biology, proteomics, and computational biology and bioinformatics. In addition, significant refinements in morphological study of the placenta and its constituent cell types have improved our ability to assess form and function in highly integrated manner. To offer an overview of modern technologies used by investigators to study the placenta, this workshop: Advanced techniques in placental biology, assembled experts who discussed fundamental principles and real time examples of four separate methodologies. Y. Sadovsky presented the principles of microRNA function as an endogenous mechanism of gene regulation. J. Robinson demonstrated the utility of correlative microscopy in which light-level and transmission electron microscopy are combined to provide cellular and subcellular views of placental cells. A. Croy provided a lecture on the use of microdissection techniques which are invaluable for isolating very small subsets of cell types for molecular analysis. Finally, G. Rice presented an overview methods on profiling of complex protein mixtures within tissue and/or fluid samples that, when refined, will offer databases that will underpin a systems approach to modern trophoblast biology.

Animals↗
PubMedDate not supplied

Differential protein expression in the cytosol fraction of an MCF-7 breast cancer cell line selected for resistance toward melphalan.

Analysis of differential protein expression in the cytosol of melphalan-resistant and -susceptible MCF-7 cell lines has been carried out using a combination of two-dimensional gel electrophoresis, mass spectrometry, and bioinformatics. Comparison of multiple digitized gel arrays detected several spots as candidates for differentially expressed proteins in melphalan-resistant MCF-7 cells. The up-regulated proteins included retinoic acid binding protein II, an isoform of the macrophage migration inhibition factor, and other unidentified proteins. The down-regulated proteins included calreticulin, cyclophin A, and an isoform of the 27 kD heat shock protein. Correlation of the differential expression of some of the proteins with acquired resistance of MCF7 cells to melphalan is discussed.

Antineoplastic Agents, Alkylating↗
PubMed2004

Taverna: a tool for the composition and enactment of bioinformatics workflows.

MOTIVATION: In silico experiments in bioinformatics involve the co-ordinated use of computational tools and information repositories. A growing number of these resources are being made available with programmatic access in the form of Web services. Bioinformatics scientists will need to orchestrate these Web services in workflows as part of their analyses. RESULTS: The Taverna project has developed a tool for the composition and enactment of bioinformatics workflows for the life sciences community. The tool includes a workbench application which provides a graphical user interface for the composition of workflows. These workflows are written in a new language called the simple conceptual unified flow language (Scufl), where by each step within a workflow represents one atomic task. Two examples are used to illustrate the ease by which in silico experiments can be represented as Scufl workflows using the workbench application.

Computational Biology↗
PubMed2003

Genomic and proteomic analysis of mitochondrial carrier proteins in Arabidopsis.

Plant mitochondria maintain metabolic communication with the cytosol through a family of carrier proteins. In Arabidopsis, a subset of 45 putative genes encoding members of this family have been identified based on generalized mitochondrial carrier features. No gene clusters are apparent and few of the predicted protein products have mitochondrial targeting sequences recognized by bioinformatic predictors. Only nine genes are currently represented by more than 10 expressed sequence tags at The Institute for Genomic Research. Analyses of public microarray experiments reveal differential expression profiles of the more highly expressed members of this gene family in different plant organs and in response to plant hormone application and environmental stresses. A comparison of this Arabidopsis carrier subset (45) to the yeast gene family (35) reveals 10 orthologous groups between the two species. Recent surveys of the Arabidopsis mitochondrial proteome by two-dimensional gel separations have not identified any of these carrier proteins, presumably because of their hydrophobicity and basicity. Isolating integral membrane proteins from Arabidopsis mitochondria, using one-dimensional electrophoresis for protein separation and tandem mass spectrometry-based sequencing of doubly charged peptides, we have unequivocally identified specific carrier gene products located in mitochondria. This approach has identified six of the nine carriers represented highly in expressed sequence tag databases: adenine nucleotide translocator (At3g8580 and At5g13490), dicarboxylate/tricarboxylate carrier (At5g19760), phosphate carrier (At5g14040), uncoupling protein (At3g54110), and a carrier gene of unknown function (At4g01100). Overall, the combined transcript and protein expression data indicates that only a small subset of the carrier family of genes provide the majority of carrier proteins of Arabidopsis mitochondria.

Arabidopsis↗
PubMed2001

Comparing function and structure between entire proteomes.

More than 30 organisms have been sequenced entirely. Here, we applied a variety of simple bioinformatics tools to analyze 29 proteomes for representatives from all three kingdoms: eukaryotes, prokaryotes, and archaebacteria. We confirmed that eukaryotes have relatively more long proteins than prokaryotes and archaes, and that the overall amino acid composition is similar among the three. We predicted that approximately 15%-30% of all proteins contained transmembrane helices. We could not find a correlation between the content of membrane proteins and the complexity of the organism. In particular, we did not find significantly higher percentages of helical membrane proteins in eukaryotes than in prokaryotes or archae. However, we found more proteins with seven transmembrane helices in eukaryotes and more with six and 12 transmembrane helices in prokaryotes. We found twice as many coiled-coil proteins in eukaryotes (10%) as in prokaryotes and archaes (4%-5%), and we predicted approximately 15%-25% of all proteins to be secreted by most eukaryotes and prokaryotes. Every tenth protein had no known homolog in current databases, and 30%-40% of the proteins fell into structural families with >100 members. A classification by cellular function verified that eukaryotes have a higher proportion of proteins for communication with the environment. Finally, we found at least one homolog of experimentally known structure for approximately 20%-45% of all proteins; the regions with structural homology covered 20%-30% of all residues. These numbers may or may not suggest that there are 1200-2600 folds in the universe of protein structures. All predictions are available at http://cubic.bioc.columbia.edu/genomes.

Amino Acids↗
PubMed2004

Protein profiling in brain tumors using mass spectrometry: feasibility of a new technique for the analysis of protein expression.

PURPOSE: The purpose of this research was to perform a preliminary assessment of protein patterns in primary brain tumors using a direct-tissue mass spectrometric technique to profile and map biomolecules. EXPERIMENTAL DESIGN: We examined 20 prospectively collected, snap-frozen normal brain and brain tumor specimens using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS), and compared peptide and protein expression in primary brain tumor and nontumor brain tissues. RESULTS: MS can be used to identify protein expression patterns in human brain tissue and tumor specimens. The mass spectral patterns can reliably identify glial neoplasms of similar histological grade and differentiate them from tumors of different histological grades as well as from nontumor brain tissues. Initial bioinformatics cluster analysis algorithms classified tumor and nontumor tissues into similar groups comparable with their histological grade. CONCLUSIONS: We describe a novel tool for the analysis of protein expression patterns in human glial neoplasms. Initial results demonstrate that MALDI-MS technology can significantly aid in the process of unraveling and understanding the molecular complexities of gliomas. MALDI-MS accurately and reliably identified normal and neoplastic tissues, and could be used to discriminate between tumors of increasing grades.

Adult↗
PubMed2005

The Gene Set Builder: collation, curation, and distribution of sets of genes.

BACKGROUND: In bioinformatics and genomics, there are many applications designed to investigate the common properties for a set of genes. Often, these multi-gene analysis tools attempt to reveal sequential, functional, and expressional ties. However, while tremendous effort has been invested in developing tools that can analyze a set of genes, minimal effort has been invested in developing tools that can help researchers compile, store, and annotate gene sets in the first place. As a result, the process of making or accessing a set often involves tedious and time consuming steps such as finding identifiers for each individual gene. These steps are often repeated extensively to shift from one identifier type to another; or to recreate a published set. In this paper, we present a simple online tool which - with the help of the gene catalogs Ensembl and GeneLynx - can help researchers build and annotate sets of genes quickly and easily. DESCRIPTION: The Gene Set Builder is a database-driven, web-based tool designed to help researchers compile, store, export, and share sets of genes. This application supports the 17 eukaryotic genomes found in version 32 of the Ensembl database, which includes species from yeast to human. User-created information such as sets and customized annotations are stored to facilitate easy access. Gene sets stored in the system can be "exported" in a variety of output formats - as lists of identifiers, in tables, or as sequences. In addition, gene sets can be "shared" with specific users to facilitate collaborations or fully released to provide access to published results. The application also features a Perl API (Application Programming Interface) for direct connectivity to custom analysis tools. A downloadable Quick Reference guide and an online tutorial are available to help new users learn its functionalities. CONCLUSION: The Gene Set Builder is an Ensembl-facilitated online tool designed to help researchers compile and manage sets of genes in a user-friendly environment. The application can be accessed via http://www.cisreg.ca/gsb/.

Computational Biology↗
PubMed2006

Intrinsic disorder and functional proteomics.

The recent advances in the prediction of intrinsically disordered proteins and the use of protein disorder prediction in the fields of molecular biology and bioinformatics are reviewed here, especially with regard to protein function. First, a close look is taken at intrinsically disordered proteins and then at the methods used for their experimental characterization. Next, the major statistical properties of disordered regions are summarized, and prediction models developed thus far are described, including their numerous applications in functional proteomics. The future of the prediction of protein disorder and the future uses of such predictions in functional proteomics comprise the last section of this article.

Algorithms↗
PubMed2005

RPBS: a web resource for structural bioinformatics.

RPBS (Ressource Parisienne en Bioinformatique Structurale) is a resource dedicated primarily to structural bioinformatics. It is the result of a joint effort by several teams to set up an interface that offers original and powerful methods in the field. As an illustration, we focus here on three such methods uniquely available at RPBS: AUTOMAT for sequence databank scanning, YAKUSA for structure databank scanning and WLOOP for homology loop modelling. The RPBS server can be accessed at http://bioserv.rpbs.jussieu.fr/ and the specific services at http://bioserv.rpbs.jussieu.fr/SpecificServices.html.

Computational Biology↗
PubMed2002

A hypergraph-based method for unification of existing protein structure- and sequence-families.

Classification of proteins is a major challenge in bioinformatics. Here an approach is presented, that unifies different existing classifications of protein structures and sequences. Protein structural domains are represented as nodes in a hypergraph. Shared memberships in sequence families result in hyperedges in the graph. The presented method partitions the hypergraph into clusters of structural domains. Each computed cluster is based on a set of shared sequence family memberships. Thus, the clusters put existing protein sequence families into the context of structural family hierarchies. Conversely, structural domains are related to their sequence family memberships, which can be used to gain further knowledge about the respective structural families.

Databases, Protein↗
PubMed2004

Hair keratin associated proteins: characterization of a second high sulfur KAP gene domain on human chromosome 21.

Analysis of the EBI/GeneBank database using nonhuman hair keratin associated protein (KAP) gene sequences as a query resulted in the identification of two human KAP gene domains on chromosome 21, one of which, located at 21q22.1, has recently been characterized. The second domain presented here, an approximately 90 kb domain on chromosome 21q23, harbored 16 KAP genes and two KAP pseudogenes. By comparison with known sheep and mouse KAP families, these genes could be assigned to two KAP families, KAP10 and KAP12, with the KAP10 family (12 members) being distinctly larger than the KAP12 family (four members). Systematic cDNA/3' rapid amplification of cDNA ends isolation studies using human scalp mRNA led to the identification of eight KAP10 and two KAP12 cDNA sequences. In situ hybridization analyses of human anagen hair follicles using specific 3'-noncoding sequences of the various KAP10/KAP12 genes revealed mRNA expression of nearly all KAP10 and KAP12 members exclusively in a narrow region of the middle portion of the hair fiber cuticle. Bioinformatic analyses of the promoter regions of the KAP10/KAP12 genes demonstrated several enhancer elements that were present in nearly all of the KAP genes. Primary among these were binding elements for the ETS, heat shock factor, AML, and HOX families of transcription factors.

Amino Acid Sequence↗
PubMed2002

The use of bioinformatics to identify the genomic structure of the gene that encodes neutrophil antigen NB1, CD177.

The gene encoding neutrophil alloantigen NB1, CD177, is highly homologous to a gene overexpressed in polycythemia vera neutrophils, polycythemia rubra vera-1 (PRV-1). The cDNAs of both genes have been cloned, but their genomic structure is unknown. The purpose of this study was to determine the intron-exon organization of NB1 and PRV-1 and discern if they are separate members of a homologous gene family or alleles of the same gene. GenBank's human genome sequences were probed in silico with PRV-1's 1605-nucleotide coding sequence. Searches identified two adjacent bacterial artificial chromosomes (BACs) on chromosome 19q13.2: BC338531 and BC52850. BC338531 contained sequences 100% homologous to the first 654 nucleotides of PRV-1. Comparison of coding and genomic sequences allowed us to separate this region into exons 1 through 5, interrupted by five introns. BC52850 contained sequences 95% homologous to nucleotides 413 through 1605 of PRV-1, organized into exons 4 through 9. However, the orientation of PRV-1-homologous in the first BAC was plus-plus and of the second was plus-minus, indicating they could not be portions of the same gene. The GenBank sequence of BC338531 was incomplete, creating a sequence gap in chromosome 19q13.2. Evaluation of BC338531's unfinished sequences in Joint Genome Institute public databases allowed us to complete the gap and revealed that BC338531 contained sequences 98% homologous to all nine PRV-1 exons followed by a second gene consisting of exons 9 through 4. Most likely, NB1 and PRV-1 are alleles of the same gene, CD177, and the duplication of exons 4 through 9 is a pseudo gene.

Amino Acid Sequence↗