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An efficient algorithm for systematic analysis of nucleotide strings suitable for siRNA design

BMC Research Notes 2011年第1期4卷 1-9页

作者： Baranova, Ancha Bode, Jonathan Manyam, Ganiraju Emelianenko, Maria School of Systems Biology George Mason University Fairfax VA United States Research Center for Medical Genetics RAMS Moscow Moskvorechie Str. 1 Russian Federation Department of Mathematical Sciences George Mason University Fairfax VA 22030 United States Bioinformatics and Computational Biology Dept. UT MD Anderson Cancer Center Houston TX United States

Background: The "off-target" silencing effect hinders the development of siRNA-based therapeutic and research applications. Existing solutions for finding possible locations of siRNA seats within a large database of genes are either too slow, miss a portion of the targets, or are simply not designed to handle a very large number of queries. We propose a new approach that reduces the computational time as compared to existing techniques. Findings. The proposed method employs tree-based storage in a form of a modified truncated suffix tree to sort all possible short string substrings within given set of strings (i.e. transcriptome). Using the new algorithm, we pre-computed a list of the best siRNA locations within each human gene ("siRNA seats"). siRNAs designed to reside within siRNA seats are less likely to hybridize off-target. These siRNA seats could be used as an input for the traditional "set-of-rules" type of siRNA designing software. The list of siRNA seats is available through a publicly available database located at http://***/∼gmanyam/siRNA-db/***. Conclusions: In attempt to perform top-down prediction of the human siRNA with minimized off-target hybridization, we developed an efficient algorithm that employs suffix tree based storage of the substrings. Applications of this approach are not limited to optimal siRNA design, but can also be useful for other tasks involving selection of the characteristic strings specific to individual genes. These strings could then be used as siRNA seats, as specific probes for gene expression studies by oligonucleotide-based microarrays, for the design of molecular beacon probes for Real-Time PCR and, generally, any type of PCR primers. © 2011 Baranova et al;licensee BioMed Central Ltd.

关键词： basic local alignment search tool Suffix Tree Storage Structure Gene String Unique Substrings

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NBC update: The addition of viral and fungal databases to the Naïve Bayes classification tool

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BMC Research Notes 2012年第1期5卷 1-5页

作者： Rosen, Gail L. Lim, Tze Department of Electrical and Computer Engineering Drexel University Philadelphia PA United States Department of Physics Drexel University Philadelphia PA United States

Background: Classifying the fungal and viral content of a sample is an important component of analyzing microbial communities in environmental media. Therefore, a method to classify any fragment from these organisms' DNA should be implemented. Results: We update the näive Bayes classification (NBC) tool to classify reads originating from viral and fungal organisms. NBC classifies a fungal dataset similarly to basic local alignment search tool (BLAST) and the Ribosomal Database Project (RDP) classifier. We also show NBC's similarities and differences to RDP on a fungal large subunit (LSU) ribosomal DNA dataset. For viruses in the training database, strain classification accuracy is 98%, while for those reads originating from sequences not in the database, the order-level accuracy is 78%, where order indicates the taxonomic level in the tree of life. Conclusions: In addition to being competitive to other classifiers available, NBC has the potential to handle reads originating from any location in the genome. We recommend using the Bacteria/Archaea, Fungal, and Virus databases separately due to algorithmic biases towards long genomes. The tool is publicly available at:. © 2012 Rosen et al;licensee BioMed Central Ltd.

关键词： Internal Transcribe Spacer basic local alignment search tool Ribosomal Database Project Fungal Sequence Ribosomal Database Project Classifier

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New finite-size correction for local alignment score distributions

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BMC Research Notes 2012年第1期5卷 1-6页

作者： Park, Yonil Sheetlin, Sergey Ma, Ning Madden, Thomas L. Spouge, John L. National Center for Biotechnology Information National Library of Medicine Bethesda MD 20894 United States

Background: local alignment programs often calculate the probability that a match occurred by chance. The calculation of this probability may require a finite-size correction to the lengths of the sequences, as an alignment that starts near the end of either sequence may run out of sequence before achieving a significant score. Findings. We present an improved finite-size correction that considers the distribution of sequence lengths rather than simply the corresponding means. This approach improves sensitivity and avoids substituting an ad hoc length for short sequences that can underestimate the significance of a match. We use a test set derived from ASTRAL to show improved ROC scores, especially for shorter sequences. Conclusions: The new finite-size correction improves the calculation of probabilities for a local alignment. It is now used in the BLAST+ package and at the NCBI BLAST web site (). © 2012Park et al.;licensee BioMed Central Ltd.

关键词： Receiver Operator Characteristic local alignment basic local alignment search tool basic local alignment search tool search Optimal local alignment

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SS-Wrapper: a package of wrapper applications for similarity searches on Linux clusters

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BMC BIOINFORMATICS 2004年第1期5卷 171-171页

作者： Wang, CL Lefkowitz, EJ Univ Alabama Birmingham Dept Microbiol Birmingham AL 35294 USA

Background: Large-scale sequence comparison is a powerful tool for biological inference in modern molecular biology. Comparing new sequences to those in annotated databases is a useful source of functional and structural information about these sequences. Using software such as the basic local alignment search tool ( BLAST) or HMMPFAM to identify statistically significant matches between newly sequenced segments of genetic material and those in databases is an important task for most molecular biologists. searching algorithms are intrinsically slow and data-intensive, especially in light of the rapid growth of biological sequence databases due to the emergence of high throughput DNA sequencing techniques. Thus, traditional bioinformatics tools are impractical on PCs and even on dedicated UNIX servers. To take advantage of larger databases and more reliable methods, high performance computation becomes necessary. Results: We describe the implementation of SS-Wrapper ( Similarity search Wrapper), a package of wrapper applications that can parallelize similarity search applications on a Linux cluster. Our wrapper utilizes a query segmentation-search (QS-search) approach to parallelize sequence database search applications. It takes into consideration load balancing between each node on the cluster to maximize resource usage. QS-search is designed to wrap many different search tools, such as BLAST and HMMPFAM using the same interface. This implementation does not alter the original program, so newly obtained programs and program updates should be accommodated easily. Benchmark experiments using QS-search to optimize BLAST and HMMPFAM showed that QS-search accelerated the performance of these programs almost linearly in proportion to the number of CPUs used. We have also implemented a wrapper that utilizes a database segmentation approach (DS-BLAST) that provides a complementary solution for BLAST searches when the database is too large to fit into the memory of a single

关键词： Query Sequence basic local alignment search tool Message Passing Interface Sequence Similarity search basic local alignment search tool search

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PLAN: a web platform for automating high-throughput BLAST searches and for managing and mining results

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BMC BIOINFORMATICS 2007年第1期8卷 53-53页

作者： He, Ji Dai, Xinbin Zhao, Xuechun Samuel Roberts Noble Fdn Inc Div Plant Biol Bioinformat Lab Ardmore OK 73401 USA

Background: BLAST searches are widely used for sequence alignment. The search results are commonly adopted for various functional and comparative genomics tasks such as annotating unknown sequences, investigating gene models and comparing two sequence sets. Advances in sequencing technologies pose challenges for high-throughput analysis of large-scale sequence data. A number of programs and hardware solutions exist for efficient BLAST searching, but there is a lack of generic software solutions for mining and personalized management of the results. Systematically reviewing the results and identifying information of interest remains tedious and time-consuming. Results: Personal BLAST Navigator (PLAN) is a versatile web platform that helps users to carry out various personalized pre- and post-BLAST tasks, including: (1) query and target sequence database management, (2) automated high-throughput BLAST searching, (3) indexing and searching of results, (4) filtering results online, (5) managing results of personal interest in favorite categories, (6) automated sequence annotation (such as NCBI NR and ontology-based annotation). PLAN integrates, by default, the Decypher hardware-based BLAST solution provided by Active Motif Inc. with a greatly improved efficiency over conventional BLAST software. BLAST results are visualized by spreadsheets and graphs and are full-text searchable. BLAST results and sequence annotations can be exported, in part or in full, in various formats including Microsoft Excel and FASTA. Sequences and BLAST results are organized in projects, the data publication levels of which are controlled by the registered project owners. In addition, all analytical functions are provided to public users without registration. Conclusion: PLAN has proved a valuable addition to the community for automated high-throughput BLAST searches, and, more importantly, for knowledge discovery, management and sharing based on sequence alignment results. The PLAN web interfa

关键词： Query Sequence basic local alignment search tool Laboratory Information Management System basic local alignment search tool search search Session

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DraGnET: Software for storing, managing and analyzing annotated draft genome sequence data

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BMC BIOINFORMATICS 2010年第1期11卷 100-100页

作者： Duncan, Stacy Sirkanungo, Ruchita Miller, Leslie Phillips, Gregory J. Iowa State Univ Dept Vet Microbiol & Prevent Med Ames IA 50011 USA Iowa State Univ Dept Comp Sci Ames IA USA Iowa State Univ Interdept Bioinformat & Computat Biol Ames IA USA

Background: New "next generation" DNA sequencing technologies offer individual researchers the ability to rapidly generate large amounts of genome sequence data at dramatically reduced costs. As a result, a need has arisen for new software tools for storage, management and analysis of genome sequence data. Although bioinformatic tools are available for the analysis and management of genome sequences, limitations still remain. For example, restrictions on the submission of data and use of these tools may be imposed, thereby making them unsuitable for sequencing projects that need to remain in-house or proprietary during their initial stages. Furthermore, the availability and use of next generation sequencing in industrial, governmental and academic environments requires biologist to have access to computational support for the curation and analysis of the data generated;however, this type of support is not always immediately available. Results: To address these limitations, we have developed DraGnET (Draft Genome Evaluation tool). DraGnET is an open source web application which allows researchers, with no experience in programming and database management, to setup their own in-house projects for storing, retrieving, organizing and managing annotated draft and complete genome sequence data. The software provides a web interface for the use of BLAST, allowing users to perform preliminary comparative analysis among multiple genomes. We demonstrate the utility of DraGnET for performing comparative genomics on closely related bacterial strains. Furthermore, DraGnET can be further developed to incorporate additional tools for more sophisticated analyses. Conclusions: DraGnET is designed for use either by individual researchers or as a collaborative tool available through Internet (or Intranet) deployment. For genome projects that require genome sequencing data to initially remain proprietary, DraGnET provides the means for researchers to keep their data in-house for analys

关键词： basic local alignment search tool Genome Sequence Data Integrate Microbial Genome Reverse Vaccinology Strain Information

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Discovering functional linkages and uncharacterized cellular pathways using phylogenetic profile comparisons: a comprehensive assessment

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BMC BIOINFORMATICS 2007年第1期8卷 173-173页

作者： Jothi, Raja Przytycka, Teresa M. Aravind, L. Natl Lib Med Natl Ctr Biotechnol Informat NIH Bethesda MD 20894 USA

Background: A widely-used approach for discovering functional and physical interactions among proteins involves phylogenetic profile comparisons (PPCs). Here, proteins with similar profiles are inferred to be functionally related under the assumption that proteins involved in the same metabolic pathway or cellular system are likely to have been co-inherited during evolution. Results: Our experimentation with E. coli and yeast proteins with 16 different carefully composed reference sets of genomes revealed that the phyletic patterns of proteins in prokaryotes alone could be adequate enough to make reasonably accurate functional linkage predictions. A slight improvement in performance is observed on adding few eukaryotes into the reference set, but a noticeable drop-off in performance is observed with increased number of eukaryotes. Inclusion of most parasitic, pathogenic or vertebrate genomes and multiple strains of the same species into the reference set do not necessarily contribute to an improved sensitivity or accuracy. Interestingly, we also found that evolutionary histories of individual pathways have a significant affect on the performance of the PPC approach with respect to a particular reference set. For example, to accurately predict functional links in carbohydrate or lipid metabolism, a reference set solely composed of prokaryotic (or bacterial) genomes performed among the best compared to one composed of genomes from all three super-kingdoms;this is in contrast to predicting functional links in translation for which a reference set composed of prokaryotic (or bacterial) genomes performed the worst. We also demonstrate that the widely used random null model to quantify the statistical significance of profile similarity is incomplete, which could result in an increased number of false-positives. Conclusion: Contrary to previous proposals, it is not merely the number of genomes but a careful selection of informative genomes in the reference set that influen

关键词： Mutual Information Similarity Score basic local alignment search tool KEGG Pathway Functional Linkage

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Protein function prediction by collective classification with explicit and implicit edges in protein-protein interaction networks

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BMC BIOINFORMATICS 2013年第12-Sup期14卷 S4-S4页

作者： Xiong, Wei Liu, Hui Guan, Jihong Zhou, Shuigeng Fudan Univ Sch Comp Sci Shanghai 200433 Peoples R China Fudan Univ Shanghai Key Lab Intelligent Informat Proc Shanghai 200433 Peoples R China Changzhou Univ Res Lab Informat Management Changzhou Jiangsu Peoples R China Tongji Univ Dept Comp Sci & Technol Shanghai 200092 Peoples R China

Background: Protein function prediction is an important problem in the post-genomic era. Recent advances in experimental biology have enabled the production of vast amounts of protein-protein interaction (PPI) data. Thus, using PPI data to functionally annotate proteins has been extensively studied. However, most existing network-based approaches do not work well when annotation and interaction information is inadequate in the networks. Results: In this paper, we proposed a new method that combines PPI information and protein sequence information to boost the prediction performance based on collective classification. Our method divides function prediction into two phases: First, the original PPI network is enriched by adding a number of edges that are inferred from protein sequence information. We call the added edges implicit edges, and the existing ones explicit edges correspondingly. Second, a collective classification algorithm is employed on the new network to predict protein function. Conclusions: We conducted extensive experiments on two real, publicly available PPI datasets. Compared to four existing protein function prediction approaches, our method performs better in many situations, which shows that adding implicit edges can indeed improve the prediction performance. Furthermore, the experimental results also indicate that our method is significantly better than the compared approaches in sparsely-labeled networks, and it is robust to the change of the proportion of annotated proteins.

关键词： Gene Ontology Prediction Performance basic local alignment search tool Annotate Protein Protein Versus

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Reanalyze unassigned reads in Sanger based metagenomic data using conserved gene adjacency

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BMC BIOINFORMATICS 2010年第1期11卷 565-565页

作者： Weng, Francis C. Su, Chien-Hao Hsu, Ming-Tsung Wang, Tse-Yi Tsai, Huai-Kuang Wang, Daryi Acad Sinica Inst Informat Sci Taipei 115 Taiwan Acad Sinica Biodivers Res Ctr Taipei 115 Taiwan Acad Sinica Res Ctr Informat Technol Innovat Taipei 115 Taiwan Natl Taiwan Univ Dept Comp Sci & Informat Engn Taipei 106 Taiwan

Background: Investigation of metagenomes provides greater insight into uncultured microbial communities. The improvement in sequencing technology, which yields a large amount of sequence data, has led to major breakthroughs in the field. However, at present, taxonomic binning tools for metagenomes discard 30-40% of Sanger sequencing data due to the stringency of BLAST cut offs. In an attempt to provide a comprehensive overview of metagenomic data, we re-analyzed the discarded metagenomes by using less stringent cut-offs. Additionally, we introduced a new criterion, namely, the evolutionary conservation of adjacency between neighboring genes. To evaluate the feasibility of our approach, we re-analyzed discarded contigs and singletons from several environments with different levels of complexity. We also compared the consistency between our taxonomic binning and those reported in the original studies. Results: Among the discarded data, we found that 23.7 +/- 3.9% of singletons and 14.1 +/- 1.0% of contigs were assigned to taxa. The recovery rates for singletons were higher than those for contigs. The Pearson correlation coefficient revealed a high degree of similarity (0.94 +/- 0.03 at the phylum rank and 0.80 +/- 0.11 at the family rank) between the proposed taxonomic binning approach and those reported in original studies. In addition, an evaluation using simulated data demonstrated the reliability of the proposed approach. Conclusions: Our findings suggest that taking account of conserved neighboring gene adjacency improves taxonomic assignment when analyzing metagenomes using Sanger sequencing. In other words, utilizing the conserved gene order as a criterion will reduce the amount of data discarded when analyzing metagenomes.

关键词： basic local alignment search tool Genomic Fragment Taxonomic Assignment Metagenomic Data Taxonomic Class

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DSD - An integrated, web-accessible database of dehydrogenase enzyme stereospecificities

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BMC BIOINFORMATICS 2005年第1期6卷 283-283页

作者： Toseland, CP McSparron, HM Flower, DR Univ Oxford Jenner Inst Compton RG20 7NN Berks England

Background: Dehydrogenase enzymes belong to the oxidoreductase class and utilise the coenzymes NAD and NADP. Stereo-selectivity is focused on the C4 hydrogen atoms of the nicotinamide ring of NAD( P). Depending upon which hydrogen is transferred at the C4 location, the enzyme is designated as A or B stereospecific. Description: The Dehydrogenase Stereospecificity Database v1.0 (DSD) provides a compilation of enzyme stereochemical data, as sourced from the primary literature, in the form of a web-accessible database. There are two search engines, a menu driven search and a BLAST search. The entries are also linked to several external databases, including the NCBI and the Protein Data Bank, providing wide background information. The database is freely available online at: http:// www. ***/DSD/ Conclusion: DSD is a unique compilation available on-line for the first time which provides a key resource for the comparative analysis of reductase hydrogen transfer stereospecificity. As databases increasingly form the backbone of science, largely complete databases such as DSD, are a vital addition.

关键词： basic local alignment search tool Nicotinamide Adenine Dinucleotide Nicotinamide Adenine Dinucleotide Phosphate Flavin Adenine Dinucleotide Nicotinamide Adenine Dinucleotide Phosphate

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