http://precedings.nature.com/subjects/bioinformatics/ Recently posted documents in Bioinformatics Nature Publishing Group en Nature Precedings http://precedings.nature.com/images/header_logo.gif http://precedings.nature.com http://precedings.nature.com/documents/3938/version/1 Two of the most significant formats for biomedical ontologies are the Open Biomedical Ontologies Format (OBOF) and the Web Ontology Language (OWL). To make it possible to translate ontologies between these two representation formats, the National Center for Biomedical Ontology (NCBO) has developed a mapping between the OBOF and OWL formats as well as inter-conversion software. The goal was to allow the sharing of tools, ontologies, and associated data between the OBOF and Semantic Web communities.OBOF does not have a formal grammar, so the NCBO had to capture its intended semantics to map it to OWL.This official NCBO mapping was used to make all OBO Foundry ontologies available in OWL. Availability: This mapping functionality can be embedded into OBO-Edit and Protégé-OWL ontology editors. This software is available at: http://bioontology.org/wiki/index.php/OboInOwl:Main_Page http://precedings.nature.com/documents/3938/version/1 Wed, 04 Nov 2009 16:35:19 UTC The NCBO OBOF to OWL Mapping hdl:10101/npre.2009.3938.1 2009-11-04 Dilvan A. Moreira Nature Precedings 2009-11-04T16:35:19Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/3932/version/1 Metabolic networks are among the most widely studied biological systems. The topology and interconnections of metabolic reactions have been well described for many species, but are not sufficient to understand how their activity is regulated in living organisms. The principles directing the dynamic organisation of reaction fluxes remain poorly understood. Cyclic structures are thought to play a central role in the homeostasis of biological systems and in their resilience to a changing environment. In this work, we investigate the role of fluxes of matter cycling in metabolic networks. First, we introduce a methodology for the computation of cyclic and acyclic fluxes in metabolic networks, adapted from an algorithm initially developed to study cyclic fluxes in trophic networks. Subsequently, we apply this methodology to the analysis of three metabolic systems, including the central metabolism of wild type and a deletion mutant of Escherichia coli, erythrocyte metabolism and the central metabolism of the bacterium Methylobacterium extorquens. The role of cycles in driving and maintaining the performance of metabolic functions upon perturbations is unveiled through these examples. This methodology may be used to further investigate the role of cycles in living organisms, their pro-activity and organisational invariance, leading to a better understanding of biological entailment and information processing. http://precedings.nature.com/documents/3932/version/1 Mon, 02 Nov 2009 17:25:38 UTC Organising metabolic networks: cycles in flux distributions hdl:10101/npre.2009.3932.1 2009-11-02 Jean-Marc Schwartz Nature Precedings 2009-11-02T17:25:38Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/3920/version/1 Tracking Parkinson’s disease (PD) symptom progression often uses the Unified Parkinson’s Disease Rating Scale (UPDRS), which requires the patient’s presence in clinic, and time-consuming physical examinations by trained medical staff. Thus, symptom monitoring is costly and logistically inconvenient for patient and clinical staff alike, also hindering recruitment for future large-scale clinical trials. Here, for the first time, we demonstrate rapid, remote replication of UPDRS assessment with clinically useful accuracy (about 7.5 UPDRS points difference from the clinicians’ estimates), using only simple, self-administered, and non-invasive speech tests. We characterize speech with signal processing algorithms, extracting clinically useful features of average PD progression. Subsequently, we select the most parsimonious model with a robust feature selection algorithm, and statistically map the selected subset of features to UPDRS using linear and nonlinear regression techniques, which include classical least squares and non-parametric classification and regression trees (CART). We verify our findings on the largest database of PD speech in existence (~6,000 recordings from 42 PD patients, recruited to a six-month, multi-centre trial). These findings support the feasibility of frequent, remote and accurate UPDRS tracking. This technology could play a key part in telemonitoring frameworks that enable large-scale clinical trials into novel PD treatments. http://precedings.nature.com/documents/3920/version/1 Thu, 29 Oct 2009 15:21:58 UTC Accurate telemonitoring of Parkinson’s disease progression by non-invasive speech tests hdl:10101/npre.2009.3920.1 2009-10-29 Nature Precedings 2009-10-29T15:21:58Z Manuscript Neuroscience Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/3917/version/1 Recently Granich et al. at the World Health Organization (WHO) concluded, using mathematical modeling, that HIV epidemics could be eliminated within a decade. They assumed all individuals would be tested annually and every infected individual (regardless of stage of infection) would be put on treatment. Based on this modeling study the WHO is considering using universal testing and treatment as an HIV elimination strategy. Here we examine the study by Granich et al. and assess its validity. We present new analyses of their model by varying assumptions and parameter values. We find that under certain very optimistic assumptions HIV elimination would be (theoretically) possible, but it would take at least 70 years. To obtain this result we assumed ~65% of symptomatic and ~20% of asymptomatic individuals would be treated per year; ARVs would reduce infectivity of treated individuals a hundred fold, and only 5% of symptomatic individuals would give up treatment per year. Even under optimistic assumptions we find elimination to be unlikely. For example, we show if ~65% of symptomatic individuals are treated per year and treated individuals are completely noninfectious, HIV will remain endemic with a prevalence of 34% and an incidence of 2% per year. We conclude that the model developed by Granich et al., when used with realistic parameter values, does not show HIV elimination is possible. However our modeling results show treatment could act as an effective prevention tool and significantly reduce transmission, even if only symptomatic individuals receive ARVs. Treatment should first, and foremost, be used for therapeutic purposes. Hence, we recommend – when resources are limited – targeting those in need of treatment. Such a strategy would be ethical, feasible and epidemiologically sound. We advise that models used as health policy tools should be carefully evaluated and their results interpreted with caution. http://precedings.nature.com/documents/3917/version/1 Thu, 29 Oct 2009 14:56:08 UTC Voluntary universal testing and treatment is unlikely to lead to HIV elimination: a modeling analysis hdl:10101/npre.2009.3917.1 2009-10-29 Nature Precedings 2009-10-29T14:56:08Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3913.1 A new approach to design a dynamic model of genes with multiple autonomous regulatory modules by evolution in silico is proposed. The approach is based on Genetic Algorithms, with new crossover operators especially designed for these purposes. The approach exploits the subbasin-portal architecture of the fitness functions suitable for this kind of evolutionary modeling. The effectiveness of the approach is demonstrated on a series of benchmark tests. http://dx.doi.org/10.1038/npre.2009.3913.1 Thu, 29 Oct 2009 10:09:24 UTC Design of a dynamic model of genes with multiple autonomous regulatory modules by evolution in silico doi:10.1038/npre.2009.3913.1 2009-10-29 Nature Precedings 2009-10-29T10:09:24Z Manuscript Biotechnology Developmental Biology Genetics & Genomics Bioinformatics Evolutionary Biology http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/3898/version/1 A bacterial strain, designated Aeromonas sp. kumar, was isolated from a water sample collected from Red tide Bloom occurred in the region of Gulf of Mannar region, Puthumadam Coast, India and the strain was identified using 16S rRNA based identification. During the sample collection, microbiology analysis was done to study the morphology of the bacteria. Pure culture of strain was maintained through out the study. DNA was isolated and sequenced using 16S rRNA primers. A length of 1452 nucleotide was sequenced and was put in public data base for obtaining accession number. The sequence was studied using MEGA 4, to estimate the evolutionary distances and to construct the Phylogenetic tree. Along with that Regulatory elements and Transcription factors were studied using BPROM tool. In genetics, a promoter is a region of DNA that facilitates the transcription of a particular gene. Promoters are typically located near the genes they regulate, on the same strand and upstream (towards the 5’ region of the sense strand). The objective of the study is to predict the regulatory elements which are -10 box, -35box and three Transcription Factors (rpoD19, rpoD17 and araC) with their binding sites in the 16S rRNA gene of Aeromonas sp. kumar. The gene bank accession number for 16S rRNA gene of Aeromonas sp. kumar is FJ896014. http://precedings.nature.com/documents/3898/version/1 Wed, 28 Oct 2009 14:41:34 UTC 16S rRNA based identification of Aeromonas sp. kumar by constructing phylogenetic tree and identification of regulatory elements from the harmful Red Tide bloom, Gulf of Mannar hdl:10101/npre.2009.3898.1 2009-10-28 P. Kumar Nature Precedings 2009-10-28T14:41:34Z Manuscript Ecology Microbiology Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3908.1 Tutorial of Identification of SSR from EST resources using online Tools http://dx.doi.org/10.1038/npre.2009.3908.1 Wed, 28 Oct 2009 13:28:25 UTC SSR – Identification from EST doi:10.1038/npre.2009.3908.1 2009-10-28 Aikkal Riju Nature Precedings 2009-10-28T13:28:25Z Presentation Biotechnology Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/3905/version/1 Context: Notwithstanding the great number of studies on the etiology and pathophysiology of schizophrenia, both issues remain far from being fully understood. Schizophrenia seems to be related to several biochemical abnormalities, which point to a multi-factor etiology and pathophysiology, as well as to the perspective that several etiologically diverse disorders might coexist within this nosographic entity. On the other hand, identical twins reveal a high concordance for schizophrenia. From that standpoint, the perspective that structurally-related proteins may play an important and yet non-deterministic role seems attractive. Among these proteins, it is suggestive that Neuregulin 1 exerts a pivotal role. Objective: This paper aims to uncover the most prominent relations that Neuregulin 1 establishes with schizophrenia. Method: Several bioinformatical methods are used in order to present: 1. A visual representation of Neuregulin 1’s main molecular pathways, associated with a discussion about their importance to schizophrenia research; 2. A new heatmap of Neuregulin 1 and its receptor’s expression in brain tissues most relevant to the understanding of schizophrenia, created after the development of new R programming scripts (described elsewhere), which facilitate the analysis of gene expression profiles in public datasets; 3. A conceptual map of the literature retrieved using the keywords ‘Neuregulin 1 and human’ in PubMed, followed by a discussion of the most relevant sub-topics. Results: Neuregulin 1 polymorphisms affect several brain tissues and contribute to the etiology and pathophysiology of schizophrenia. Suggestively, Neuregulin 1 partially bridges the ‘molecular gap’ that schizophrenia establishes in relation to bipolar disorder and Alzheimer disease, which involves genes that affect several brain networks, at the same time that they are highly dependent on noxious environmental variables to be triggered. http://precedings.nature.com/documents/3905/version/1 Wed, 28 Oct 2009 11:15:17 UTC The Role of Neuregulin 1 in Schizophrenia: A Bioinformatics Approach hdl:10101/npre.2009.3905.1 2009-10-28 Alvaro M. Dias Nature Precedings 2009-10-28T11:15:17Z Manuscript Genetics & Genomics Neuroscience Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3900.1 Analyzing of sequences similarities is the first and most important method used to find out the function of unknown nucleotides. Searching of homologs should be done carefully not to loose any important ones. Having thousands of results from various long-read sequencing projects (ie. differentially expressed tags, genomic polymorphons or BAC ends), the by-hand ability to retrieve interesting (to our goal) similarities in hundreds of Blast results decreases rapidly. Decreasing the number of retrieved sequences by giving more stringency in e-value threshold or displaying less results could lead to false deductions. Functional genomics, proteomics and metabolomics could give us answers to the role of nucleotide sequences. It makes the need to annotate as much of the homologies as we can, to proper molecular function, biological process and cellular component (as its proposed by widely accepted Gene Ontology Consortium annotations or MapMan mappings by Max-Planc-Institute). To facilitate fast retrieval of interesting Blast homologies and making right deductions about the biological role of sequences, in big sequencing projects, the new Perl script BRAGOMAP was written. The program make use of some of BioPerl modules as well as the power of regex text-mining in the Perl itself. The script gives us the possibility to find interesting sequence similarities by using keywords and giving points for each one found. It collects all important information from the GenBank data and puts it in different columns of tab-delimited file for further use. If we were interested (for example) in flower differentiation genes we could use the keywords (flower, ovule, anther, etc.) and/or filter all the homologies isolated from flower tissues in a special development stage. We can also filter results by choosing similarities to interesting genes or protein products. This script retrieve also all standard information from the Blast and GenBank files as Description, ACC no., E-value, Similarity positions, Query Length, Percent of Similarity etc. Automatic GO and MapMan annotations are done by looking for genes, protein products and /or DB references in the proper mappings files. Here we present the usefulness of the script in analyzing sequence similarities and annotations mapping of 3855 BAC ends obtained from the HindIII BAC genomic library of cucumber (Cucumis sativus L., line B10). http://dx.doi.org/10.1038/npre.2009.3900.1 Mon, 26 Oct 2009 11:35:28 UTC BRAGOMAP – a new Perl script for high throughoutput blast results analysis including GO and MapMan automatic annotations doi:10.1038/npre.2009.3900.1 2009-10-26 Rafal Woycicki Nature Precedings 2009-10-26T11:35:28Z Poster Genetics & Genomics Bioinformatics Plant Biology http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/3874/version/1 This study leads to a new algebra. An algebra is defined on the common mechanisms of chromosomal mutation. The algebra (SΨ(C), *, ’, Δ, D) is constructed for a given C and Ψ. This algebra represents the most common chromosomal mutational mechanisms. This can lead to a new way to manipulate chromosomal mutation with higher structures of abstract mathematics. The first proposal of the algebra was reported in Mazumdar et al., 2007. http://precedings.nature.com/documents/3874/version/1 Tue, 20 Oct 2009 16:41:18 UTC Chromosomal mutational algebra: a new algebra to manipulate chromosomal mutation hdl:10101/npre.2009.3874.1 2009-10-20 Dipankar Mazumdar Nature Precedings 2009-10-20T16:41:18Z Manuscript Genetics & Genomics Bioinformatics http://creativecommons.org/licenses/by/3.0/