Browsing by Author "Yu, Chenggang"
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- 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
- 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 method for automatic identification of reliable heart rates calculated from ECG and PPG waveforms.(2006-05-03) Yu, Chenggang; Liu, Zhenqiu; McKenna, Thomas; Reisner, Andrew T; Reifman, JaquesThe development and application of data driven decision support systems for medical triage diagnostics and prognostics pose special requirements on physiologic data In particular that data are reliable in order to produce meaningful results The authors describe a method that automatically estimates the reliability of reference heart rates HRr derived from electrocardiogram ECG waveforms and photoplethysmogram PPG waveforms recorded by vital signs monitors The reliability is quantitatively expressed through a quality index QI for each HRr
- ItemA systems biology strategy to identify molecular mechanisms of action and protein indicators of traumatic brain injury.(2014-12-17) Yu, Chenggang; Boutté, Angela; Yu, Xueping; Dutta, Bhaskar; Feala, Jacob D; Schmid, Kara; Dave, Jitendra; Tawa, Gregory J; Wallqvist, Anders; Reifman, JaquesThe multifactorial nature of traumatic brain injury TBI especially the complex secondary tissue injury involving intertwined networks of molecular pathways that mediate cellular behavior has confounded attempts to elucidate the pathology underlying the progression of TBI Here systems biology strategies are exploited to identify novel molecular mechanisms and protein indicators of brain injury To this end we performed a meta analysis of four distinct high throughput gene expression studies involving different animal models of TBI By using canonical pathways and a large human protein interaction network as a scaffold we separately overlaid the gene expression data from each study to identify molecular signatures that were conserved across the different studies At 24 hr after injury the significantly activated molecular signatures were nonspecific to TBI whereas the significantly suppressed molecular signatures were specific to the nervous system In particular we identified a suppressed subnetwork consisting of 58 highly interacting coregulated proteins associated with synaptic function We selected three proteins from this subnetwork postsynaptic density protein 95 nitric oxide synthase 1 and disrupted in schizophrenia 1 and hypothesized that their abundance would be significantly reduced after TBI In a penetrating ballistic like brain injury rat model of severe TBI Western blot analysis confirmed our hypothesis In addition our analysis recovered 12 previously identified protein biomarkers of TBI The results suggest that systems biology may provide an efficient high yield approach to generate testable hypotheses that can be experimentally validated to identify novel mechanisms of action and molecular indicators of TBI