Physical Sciences and Mathematics Commons^™

Crosstalk Among Lncrnas, Micrornas And Mrnas In The Muscle ‘Degradome’ Of Rainbow Trout, Bam Paneru, Ali Ali, Rafet Al-Tobasei, Brett Kenney, Mohamed Salem

Faculty & Staff Scholarship

In fish, protein-coding and noncoding genes involved in muscle atrophy are not fully characterized. In this study, we characterized coding and noncoding genes involved in gonadogenesis-associated muscle atrophy, and investigated the potential functional interplay between these genes. Using RNA- Seq, we compared expression pattern of mRNAs, long noncoding RNAs (lncRNAs) and microRNAs of atrophying skeletal muscle from gravid females and control skeletal muscle from age-matched sterile individuals. A total of 852 mRNAs, 1,160 lncRNAs and 28 microRNAs were differentially expressed (DE) between the two groups. Muscle atrophy appears to be mediated by many genes encoding ubiquitin- proteasome system, autophagy related …

Distributed Gene Clinical Decision Support System Based On Cloud Computing, Bo Xu, Changlong Li, Hang Zhuang, Jiali Wang, Qingfeng Wang, Chao Wang, Xuehai Zhou

Faculty & Staff Scholarship

Background: The clinical decision support system can effectively break the limitations of doctors’ knowledge and reduce the possibility of misdiagnosis to enhance health care. The traditional genetic data storage and analysis methods based on stand-alone environment are hard to meet the computational requirements with the rapid genetic data growth for the limited scalability.

Methods: In this paper, we propose a distributed gene clinical decision support system, which is named GCDSS. And a prototype is implemented based on cloud computing technology. At the same time, we present CloudBWA which is a novel distributed read mapping algorithm leveraging batch processing strategy to …

Genome-Wide Association Analysis With A 50k Transcribed Gene Snp-Chip Identifies Qtl Affecting Muscle Yield In Rainbow Trout, Mohamed Salem, Rafet Al-Tobasei, Ali Ali, Daniela Lourenco, Guangtu Gao, Yniv Palti, Brett Kenney, Timothy D. Leeds

Faculty & Staff Scholarship

Detection of coding/functional SNPs that change the biological function of a gene may lead to identification of putative causative alleles within QTL regions and discovery of genetic markers with large effects on phenotypes. This study has two-fold objectives, first to develop, and validate a 50K transcribed gene SNP-chip using RNA-Seq data. To achieve this objective, two bioinformatics pipelines, GATK and SAMtools, were used to identify ∼21K transcribed SNPs with allelic imbalances associated with important aquaculture production traits including body weight, muscle yield, muscle fat content, shear force, and whiteness in addition to resistance/susceptibility to bacterial cold-water disease (BCWD). SNPs ere …

Integrated Analysis Of Lncrna And Mrna Expression In Rainbow Trout Families Showing Variation In Muscle Growth And Fillet Quality Traits, Ali Ali, Rafet Al-Tobasei, Brett Kenney, Timothy D. Leeds, Mohamed Salem

Faculty & Staff Scholarship

Muscle yield and quality traits are important for the aquaculture industry and consumers. Genetic selection for these traits is difficult because they are polygenic and result from multifactorial interactions. To study the genetic architecture of these traits, phenotypic characterization of whole body weight (WBW), muscle yield, fat content, shear force and whiteness were measured in ~500 fish representing 98 families from a growth-selected line. RNA-Seq was used to sequence the muscle transcriptome of different families exhibiting divergent phenotypes for each trait. We have identified 240 and 1,280 differentially expressed (DE) protein-coding genes and long noncoding RNAs (lncRNAs), respectively, in fish …

Adverse Event Detection By Integrating Twitter Data And Vaers, Junxiang Wang, Liang Zhao, Yanfang Ye, Yuji Zhang

Faculty & Staff Scholarship

Background: Vaccinehasbeenoneofthemostsuccessfulpublichealthinterventionstodate.However,vaccines are pharmaceutical products that carry risks so that many adverse events (AEs) are reported after receiving vaccines. Traditional adverse event reporting systems suffer from several crucial challenges including poor timeliness. This motivates increasing social media-based detection systems, which demonstrate successful capability to capture timely and prevalent disease information. Despite these advantages, social media-based AE detection suffers from serious challenges such as labor-intensive labeling and class imbalance of the training data.

Results: Totacklebothchallengesfromtraditionalreportingsystemsandsocialmedia,weexploittheircomplementary strength and develop a combinatorial classification approach by integrating Twitter data and the Vaccine Adverse Event Reporting System (VAERS) information aiming to identify potential AEs after …

Cluster-Based Network Proximities For Arbitrary Nodal Subsets, Kenneth S. Berenhaut, Peter S. Barr, Alyssa M. Kogel, Ryan L. Melvin

Faculty & Staff Scholarship

The concept of a cluster or community in a network context has been of considerable interest in a variety of settings in recent years. In this paper, employing random walks and geodesic distance, we introduce a unified measure of cluster-based proximity between nodes, relative to a given subset of interest. The inherent simplicity and informativeness of the approach could make it of value to researchers in a variety of scientific fields. Applicability is demonstrated via application to clustering for a number of existent data sets (including multipartite networks). We view community detection (i.e. when the full set of network nodes …