Browsing by Author "Zavaljevski, Nela"
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- Item16S rRNA gene pyrosequencing of reference and clinical samples and investigation of the temperature stability of microbiome profiles.(2014-09-17) Hang, Jun; Desai, Valmik; Zavaljevski, Nela; Yang, Yu; Lin, Xiaoxu; Satya, Ravi Vijaya; Martinez, Luis J; Blaylock, Jason M; Jarman, Richard G; Thomas, Stephen J; Kuschner, Robert ASample storage conditions extraction methods PCR primers and parameters are major factors that affect metagenomics analysis based on microbial 16S rRNA gene sequencing Most published studies were limited to the comparison of only one or two types of these factors Systematic multi factor explorations are needed to evaluate the conditions that may impact validity of a microbiome analysis This study was aimed to improve methodological options to facilitate the best technical approaches in the design of a microbiome study Three readily available mock bacterial community materials and two commercial extraction techniques Qiagen DNeasy and MO BIO PowerSoil DNA purification methods were used to assess procedures for 16S ribosomal DNA amplification and pyrosequencing based analysis Primers were chosen for 16S rDNA quantitative PCR and amplification of region V3 to V1 Swabs spiked with mock bacterial community cells and clinical oropharyngeal swabs were incubated at respective temperatures of 80 C 20 C 4 C and 37 C for 4 weeks then extracted with the two methods and subjected to pyrosequencing and taxonomic and statistical analyses to investigate microbiome profile stability
- ItemAGeS: a software system for microbial genome sequence annotation.(2011-03-16) Kumar, Kamal; Desai, Valmik; Cheng, Li; Khitrov, Maxim; Grover, Deepak; Satya, Ravi Vijaya; Yu, Chenggang; Zavaljevski, Nela; Reifman, JaquesThe annotation of genomes from next generation sequencing platforms needs to be rapid high throughput and fully integrated and automated Although a few Web based annotation services have recently become available they may not be the best solution for researchers that need to annotate a large number of genomes possibly including proprietary data and store them locally for further analysis To address this need we developed a standalone software application the Annotation of microbial Genome Sequences AGeS system which incorporates publicly available and in house developed bioinformatics tools and databases many of which are parallelized for high throughput performance
- ItemDBSecSys: a database of Burkholderia mallei secretion systems.(2014-07-25) Memišević, Vesna; Kumar, Kamal; Cheng, Li; Zavaljevski, Nela; DeShazer, David; Wallqvist, Anders; Reifman, JaquesBacterial pathogenicity represents a major public health concern worldwide Secretion systems are a key component of bacterial pathogenicity as they provide the means for bacterial proteins to penetrate host cell membranes and insert themselves directly into the host cells cytosol Burkholderia mallei is a Gram negative bacterium that uses multiple secretion systems during its host infection life cycle To date the identities of secretion system proteins for B mallei are not well known and their pathogenic mechanisms of action and host factors are largely uncharacterized
- ItemThe development of PIPA: an integrated and automated pipeline for genome-wide protein function annotation.(2008-03-03) Yu, Chenggang; Zavaljevski, Nela; Desai, Valmik; Johnson, Seth; Stevens, Fred J; Reifman, JaquesAutomated protein function prediction methods are needed to keep pace with high throughput sequencing With the existence of many programs and databases for inferring different protein functions a pipeline that properly integrates these resources will benefit from the advantages of each method However integrated systems usually do not provide mechanisms to generate customized databases to predict particular protein functions Here we describe a tool termed PIPA Pipeline for Protein Annotation that has these capabilities
- ItemGenome-wide enzyme annotation with precision control: catalytic families (CatFam) databases.(2008-12-24) Yu, Chenggang; Zavaljevski, Nela; Desai, Valmik; Reifman, JaquesIn this article we present a new method termed CatFam Catalytic Families to automatically infer the functions of catalytic proteins which account for 20 40 of all proteins in living organisms and play a critical role in a variety of biological processes CatFam is a sequence based method that generates sequence profiles to represent and infer protein catalytic functions CatFam generates profiles through a stepwise procedure that carefully controls profile quality and employs nonenzymes as negative samples to establish profile specific thresholds associated with a predefined nominal false positive rate FPR of predictions The adjustable FPR allows for fine precision control of each profile and enables the generation of profile databases that meet different needs function annotation with high precision and hypothesis generation with moderate precision but better recall Multiple tests of CatFam databases generated with distinct nominal FPRs against enzyme and nonenzyme datasets show that the method s predictions have consistently high precision and recall For example a 1 FPR database predicts protein catalytic functions for a dataset of enzymes and nonenzymes with 98 6 precision and 95 0 recall Comparisons of CatFam databases against other established profile based methods for the functional annotation of 13 bacterial genomes indicate that CatFam consistently achieves higher precision and in most cases higher recall and that on average CatFam provides 21 9 additional catalytic functions not inferred by the other similarly reliable methods These results strongly suggest that the proposed method provides a valuable contribution to the automated prediction of protein catalytic functions The CatFam databases and the database search program are freely available at http www bhsai org downloads catfam tar gz
- ItemA high-throughput pipeline for designing microarray-based pathogen diagnostic assays.(2008-04-30) Vijaya Satya, Ravi; Zavaljevski, Nela; Kumar, Kamal; Reifman, JaquesWe present a methodology for high throughput design of oligonucleotide fingerprints for microarray based pathogen diagnostic assays The oligonucleotide fingerprints or DNA microarray probes are designed for identifying target organisms in environmental or clinical samples The design process is implemented in a high performance computing software pipeline that incorporates major algorithmic improvements over a previous version to both reduce computation time and improve specificity assessment
- ItemOligonucleotide fingerprint identification for microarray-based pathogen diagnostic assays.(2006-12-20) Tembe, Waibhav; Zavaljevski, Nela; Bode, Elizabeth; Chase, Catherine; Geyer, Jeanne; Wasieloski, Leonard; Benson, Gary; Reifman, JaquesAdvances in DNA microarray technology and computational methods have unlocked new opportunities to identify DNA fingerprints i e oligonucleotide sequences that uniquely identify a specific genome We present an integrated approach for the computational identification of DNA fingerprints for design of microarray based pathogen diagnostic assays We provide a quantifiable definition of a DNA fingerprint stated both from a computational as well as an experimental point of view and the analytical proof that all in silico fingerprints satisfying the stated definition are found using our approach