2009 Ohio Collaborative Conference on Bioinformatics最新文献

{"title":"A Comparision of Codon Usage Trends in Prokaryotes","authors":"A. Hanes, M. Raymer, T. Doom, D. Krane","doi":"10.1109/OCCBIO.2009.26","DOIUrl":"https://doi.org/10.1109/OCCBIO.2009.26","url":null,"abstract":"Codon usage bias is an effective measure of the differences among organisms at a genomic level. These genomic differences also reflect some differences in the organisms’ lifestyles and physiology. Here we demonstrate that prokaryotic obligate intracellular parasites and symbionts have a codon usage pattern that differs significantly from that of exclusively free-living prokaryotes. This result is valuable in that it suggests that the habitat of an organism may directly influence that organism’s use of synonymous codons, which in turn demonstrates evidence of an evolutionary mechanism that operates at a finer molecular level than that of amino acids and proteins.","PeriodicalId":231499,"journal":{"name":"2009 Ohio Collaborative Conference on Bioinformatics","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133335724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding Sequence Variability of RNA Motifs Using Geometric Search and IsoDiscrepancy Matrices","authors":"Anton I. Petrov, Jesse Stombaugh, Craig L. Zirbel, N. Leontis","doi":"10.1109/OCCBIO.2009.15","DOIUrl":"https://doi.org/10.1109/OCCBIO.2009.15","url":null,"abstract":"Many of the nominally single-stranded hairpin, internal, and junction “loop” regions of RNA secondary structures, in fact, form uniquely folded 3D motifs. These elements are largely structured by non-Watson-Crick basepairs. Many 3D motifs are recurrent, meaning they occur in different RNAs. Recurrent motifs have the same 3D structure but not necessarily the same sequence. We describe a methodology for identifying the sequence variability of a given recurrent RNA internal loop that can be generalized to hairpin and junction loops. Since the database of RNA 3D structures now contains a significant number of biologically active, structured RNAs, including ribosomal RNAs, ribozymes, and riboswitches, we can directly observe some of the sequence variability for recurrent motifs in x-ray crystal structures. We use our search program, FR3D, to search the 3D structure database for geometrically similar motif instances that share the same spatial pattern of basepairs. We apply our analysis of RNA basepair isostericity and occurrence frequencies to suggest likely basepair substitutions. We use the IsoDiscrepancy Index (IDI), which we recently introduced to quantify basepair isostericities, to derive 4x4 IDI Tables for each base combination in each basepair family. We illustrate how these tables can be applied to predict the most likely base substitutions that occur in a 3D motif. By comparing observed motif instances, we also determine the most likely locations of inserted (\"bulged\") nucleotides. We compare the predictions from these considerations to observed variability in multiple sequence alignments of the motif.","PeriodicalId":231499,"journal":{"name":"2009 Ohio Collaborative Conference on Bioinformatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131344081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of a Breast Cancer Associated Regulatory Network","authors":"J. Parvin, Zeina Kais, M. Arora, S. Kotian, Alicia Zha, Derek J. R. Ransburgh, Doruk Bozdag, Ümit V. Çatalyürek, Kun Huang","doi":"10.1109/OCCBIO.2009.37","DOIUrl":"https://doi.org/10.1109/OCCBIO.2009.37","url":null,"abstract":"We are developing a new framework for discovery of genes involved in the breast carcinogenesis process. Among families that have a predisposition to breast cancer, approximately 25% have inherited mutations in either breast cancer associated (“BRCA”) genes BRCA1 or BRCA2, but the predisposing mutated genes in the majority of the families are unknown. BRCA1 and BRCA2 gene products both regulate cellular pathways that involve DNA repair and centrosome duplication, and their expression is correlated in microarray analyses in many cell types. We hypothesize that other unidentified BRCA genes may be involved in the same pathways that BRCA1 and BRCA2 regulate, and thus may be discovered by identifying genes whose expression also is correlated with that of BRCA1 and BRCA2. We interrogate public-domain gene expression databases using newly developed computational tools that include combinatorial and algebraic clustering methods to identify genes whose expression correlates with these tumor suppressors. Identified genes are then tested in the laboratory. RNA interference is used to disrupt the expression of the candidate BRCA gene products in two different cell-based assays that are dependent on BRCA1 and BRCA2 expression. The first assay models the regulation of homology-directed recombination repair of double-strand DNA breaks, and the second assay tests the control of duplication of the centrosome. We have selected nine genes that tightly cluster with BRCA1 and BRCA2 expression in multiple datasets, and these nine genes have never before been linked with the two reference genes. When tested in the lab using RNA interference to deplete the specific protein, six of these genes were found to affect homologous recombination and four affected the regulation of centrosome number. If the informatics analysis is considered a screening tool to find genes/proteins involved in breast carcinogenesis, then this approach has an extremely high success rate in finding proteins that impact phenotypes regulated by BRCA1 and BRCA2. In summary, we employ a novel experimental framework that develops new bioinformatic tools for identifying candidate genes whose regulation suggests the potential for involvement in breast carcinogenesis, and we validate the gene in the lab. This experimental framework may also be applicable to the identification of networks of genes involved in common pathways in other disease processes.","PeriodicalId":231499,"journal":{"name":"2009 Ohio Collaborative Conference on Bioinformatics","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133215932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Uncovering Androgen Responsive Regulatory Networks in Prostate Cancer","authors":"Kurtis Eisermann, A. Bazarov, Adina Brett, Ethan Knapp, H. Piontkivska, G. Fraizer","doi":"10.1109/OCCBIO.2009.21","DOIUrl":"https://doi.org/10.1109/OCCBIO.2009.21","url":null,"abstract":"An important goal for prostate cancer therapy is to identify novel mechanisms of androgen signaling that may provide new targets for androgen blockade therapy. Androgen regulated target genes continue to be identified, and include genes with regulatory regions containing 1) classical dimeric androgen receptor elements, or 2) sites for other transcription factors that tether androgen receptor to a regulatory region lacking androgen receptor binding sites, or 3) non-canonical half-sites. The latter category of half-sites is becoming increasingly important, because up to 80% of potential androgen receptor regulatory regions identified by chromatin immunoprecipitation microarray technology contain these monomeric half-sites [1-3]. Determining which of these predicted target genes and androgen pathways are functional is very important, as they contribute to our understanding of prostate cancer progression. Microarray analyses were used to identify genes expressed in laser captured prostate cancer epithelial cells [4], leading to identification of pathways of co-regulated genes. It is expected that important regulatory regions would be conserved between mammalian genomes, thus, comparative evolutionary analyses were used to identify evolutionary conserved transcription factor binding sites [5]. Notably, non-canonical androgen receptor half-sites were identified in a majority of the gene promoters analyzed, and these sites were adjacent to evolutionary conserved zinc finger transcription factor sites. Subsequent ChIP assays showed that indeed SP1, WT1 and AR proteins all bind to a common regulatory region, indicating potential for interaction between these transcription factors that in turn can modulate hormone responsiveness. Overall, our bioinformatics screening coupled with experimental validation has revealed critical components of regulatory networks important in prostate cancer cells and disease progression.","PeriodicalId":231499,"journal":{"name":"2009 Ohio Collaborative Conference on Bioinformatics","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115832477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"TIGERA: A New Tool for Illumina Gene Expression Reads Analysis","authors":"Xiaodong Bai, P. Grewal","doi":"10.1109/OCCBIO.2009.14","DOIUrl":"https://doi.org/10.1109/OCCBIO.2009.14","url":null,"abstract":"Next-generation sequencing platforms, including Illumina, 454, and SOLiD are emerging as easier, faster, and cheaper alternatives to traditional sequencing platforms. Illumina digital gene expression (DGE) tag profiling allows comprehensive analysis of differentially expressed genes in organisms. Computer programs are necessary to handle the overwhelming amount of data generated by the Illumina Genome Analyzer. Here we report the design and implementation of a program for the analysis of differential gene expression based on Illumina data. The program TIGERA (Tool for Illumina Gene Expression Reads Analysis) was written in perl utilizing newly-implemented and preexisting algorithms with a simple graphical user interface. The program performs the following tasks automatically after the required inputs are provided. The expression levels of high-quality Illumina tags for each of the two groups of libraries are determined and normalized as transcript per million (TPM). The Illumina tags are mapped to the annotated reference sequences to identify uniquely mapped tags. The mapping results are validated using information generated by digital restriction enzyme digestion of the reference sequences. Based on whether the tags matched to unique or multiple reference sequences after validation, the tags are grouped in three categories: one tag-one reference, one tag-one gene, and one tag-multiple genes. The tags within the first two categories are analyzed further to determine the reference sequences that contain unique expression levels or have potential alternative transcript splicing products. A Poisson mixture model is applied to analyze the differential expression of reference sequences with unique expression levels and the tags not being matched to the reference sequences. The progress of the analysis is monitored and reported. The analysis results are presented as text files and also deposited in a MySQL database that can be visualized and searched in Internet browsers. Two biological replicates of the DGE tag libraries of the infective juveniles of the entomopathogenic nematode Heterorhabditis bacteriophora TT01 and GPS11 strains were sequenced using Illumina platform to demonstrate the performance of the program.","PeriodicalId":231499,"journal":{"name":"2009 Ohio Collaborative Conference on Bioinformatics","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117048220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantile Scores for Combining Results from Different Microarray Platforms","authors":"S. Khuder, P. Bazeley","doi":"10.1109/OCCBIO.2009.16","DOIUrl":"https://doi.org/10.1109/OCCBIO.2009.16","url":null,"abstract":"Due to the small number of replicates in typical gene microarray experiments, the performance of statistical inference is often unsatisfactory. In this article, we present a scoring scheme, based on quantiles, that allows researchers to combine data from different platforms. We have applied the discrete-continuous normal distribution (DISCO) using the quantile scores on two publicly available data sets. Differentially expressed genes identified by DISCO are comparable to those identified by significance analysis of microarray (SAM) or Wilcoxon rank test. An algorithm based on DISCO and quantile scores is developed to combine results from Affymetrix and Illumina. Our results indicate that combining microarray data from different platforms is possible and straightforward.AVAILABILITY: R code implementing our methods is available from the authors.","PeriodicalId":231499,"journal":{"name":"2009 Ohio Collaborative Conference on Bioinformatics","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123746177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computational Challenges and Solutions to the Analysis of Micro RNA Profiles in Virally-Infected Cells Derived by Massively Parallel Sequencing","authors":"Terry Camerlengo, Gulcin H. Ozer, Guojuan Zhang, T. Joobeur, T. Meulia, J. Trgovcich, Kun Huang","doi":"10.1109/OCCBIO.2009.24","DOIUrl":"https://doi.org/10.1109/OCCBIO.2009.24","url":null,"abstract":"In this paper we report an ongoing project for identifying human cytomegalovirus (HCMV) micro RNAs (miRNA) expressed in infected human cells using the new massive parallel sequencing technology with the Solexa Sequencer. We developed a data processing pipeline for analyzing such data including mapping segments to genomes, detecting highly expressed sequences and their loci, comparing sequences to existing databases and selecting candidate miRNAs for experimental validation. We identified 114 putative virally-derived miRNAs with high expression levels that included 9 out of 10 known HCMV miRNAs, partially validating our methods. This observation also suggested that other identified sequences with high level of expression are potential miRNAs and this method is an effective way of discovering new small regulatory RNAs. Validation of putative novel viral miRNAs are underway, as are efforts to identify primary transcripts or introns from which they are derived. Future directions include designing the most statistically robust selection criteria, designing methods to measure viral-induced changes in the human miRNA expression profile, and identifying the targets of the miRNAs in the viral and human genomes.","PeriodicalId":231499,"journal":{"name":"2009 Ohio Collaborative Conference on Bioinformatics","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131418764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Evolution of Multidrug Resistance in a Hospital Pathogen","authors":"M. Adams","doi":"10.1109/OCCBIO.2009.10","DOIUrl":"https://doi.org/10.1109/OCCBIO.2009.10","url":null,"abstract":"The recent emergence of multidrug resistance(MDR) in Acinetobacter baumannii has raised concern inhealthcare settings worldwide. In order to understand therepertoire of resistance determinants and their organizationand origins, we compared the genome sequences of threeMDR and three drug-susceptible A. baumannii isolates. Theentire MDR phenotype can be explained by the acquisitionof discrete resistance determinants distributed throughoutthe genome. A resistance island (RI) with a variablecomposition of resistance determinants interspersed withtransposons, integrons, and other mobile genetic elements isa significant, but not universal, contributor to the MDRphenotype. Variable resistance gene composition amongidentical clone types from a single outbreak suggestsdynamic and active horizontal transfer. 475 genes areshared among all six clinical isolates, but absent from therelated environmental species Acinetobacter baylyi ADP1.These genes are enriched for transcription factors andtransporters and suggest physiological features of A.baumannii that are related to adaptation for growth inassociation with humans.","PeriodicalId":231499,"journal":{"name":"2009 Ohio Collaborative Conference on Bioinformatics","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115436212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond Identity- When Classical Homology Searching Fails, Why, and What you Can do About It","authors":"William C. Ray, H. Ozer, David W. Armbruster, C. Daniels","doi":"10.1109/OCCBIO.2009.23","DOIUrl":"https://doi.org/10.1109/OCCBIO.2009.23","url":null,"abstract":"Multiple Sequence Alignments of both protein and nucleic-acid sequences are a ubiquitous method for modeling sequence families that pervades every biological domain. Despite their utility, MSAs and methods derived from them fail to capture interpositional relationships that can be as critical to family membership as are positional identities.We have recently developed novel methods, MAVL and StickWRLD, to quantitate and visualize additional features of sequence family models, and have identi?ed interpositional dependencies at the residue level that are critical indicators of family membership in many sequence families. Some of these dependencies cannot be modeled by any existing modeling method, including Hidden Markov Models. In certain cases, the dependencies are suf?ciently strong that all common methods score sequences that are explicitly excluded from the family, as better candidates than any actual members.The tRNA intron-endonuclease targets in the Archaea are such a family. Originally characterized as excised introns from archaeal tRNAs, some of which function as guide RNAs to target O-methylation of the ribosomal RNAs, these sequences have a very short characteristic signature and allow signi?- cant divergence. There is insuf?cient information in the base conservation to create useful scoring models. Using our tools we have identi?ed critical residue interdependencies within the endonuclease target that enable detection of introns in whole- genomic sequence. Many of these introns occur outside tRNAs, including some that are excised from protein mRNA. The dependencies we identify correspond to a Markov network of relationships over the positional identities. The contribution of each node’s Markov blanket is incorporated via blending with the positional conservation using a voting algorithm. In this paper we present the results of this analysis and the generalization of our modeling method to arbitrary RNA families. This generalization allows development of models of similar power for arbitrary RNA families.","PeriodicalId":231499,"journal":{"name":"2009 Ohio Collaborative Conference on Bioinformatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129026553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving Functional Module Detection","authors":"K. J. Abraham, K. Sameith, F. Falciani","doi":"10.1109/OCCBIO.2009.11","DOIUrl":"https://doi.org/10.1109/OCCBIO.2009.11","url":null,"abstract":"There has been a great deal of recent interest in identifying functional modules from protein interaction and gene expression data. One commonly used computational technique is simulated annealing, which while asymptotically correct frequently suffers from slow convergence. In this paper we outline and exploit the analogy between finding functional modules and finding Haplotype Blocks from genetic data, to investigate a new technique for finding functional modules which does not rely on Monte Carlo methodology. We discuss circumstances under which our algorithm may work, but under which simulated annealing may not converge to known modules. We also suggest how our methodology might supplement, and improve the performance, of existing Monte Carlo searches.","PeriodicalId":231499,"journal":{"name":"2009 Ohio Collaborative Conference on Bioinformatics","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125085169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}