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Full-Text Articles in Genomics
Draft Genome Sequences Of Six Different Staphylococcus Epidermidis Clones, Isolated Individually From Preterm Neonates Presenting With Sepsis At Edinburgh's Royal Infirmary, Paul Walsh, M. Bekaert, J. Carroll, T. Manning, B. Kelly, A. O'Driscoll, X. Lu, C. Smith, P. Dickinson, K. Templeton, P. Ghazal, Roy D. Sleator
Draft Genome Sequences Of Six Different Staphylococcus Epidermidis Clones, Isolated Individually From Preterm Neonates Presenting With Sepsis At Edinburgh's Royal Infirmary, Paul Walsh, M. Bekaert, J. Carroll, T. Manning, B. Kelly, A. O'Driscoll, X. Lu, C. Smith, P. Dickinson, K. Templeton, P. Ghazal, Roy D. Sleator
Department of Biological Sciences Publications
Herein, we report the draft genome sequences of six individual Staphylococcus epidermidis clones, cultivated from blood taken from different preterm neonatal sepsis patients at the Royal Infirmary, Edinburgh, Scotland, United Kingdom.
Genome-Wide Sequencing Of Small Rnas Reveals A Tissue-Specific Loss Of Conserved Microrna Families In Echinococcus Granulosus, Yun Bai, Zhuangzhi Zhang, Lei Jin, Hui Kang, Yongquiang Zhu, Lu Zhang, Xia Li, Fengshou Ma, Li Zhao, Et Al.
Genome-Wide Sequencing Of Small Rnas Reveals A Tissue-Specific Loss Of Conserved Microrna Families In Echinococcus Granulosus, Yun Bai, Zhuangzhi Zhang, Lei Jin, Hui Kang, Yongquiang Zhu, Lu Zhang, Xia Li, Fengshou Ma, Li Zhao, Et Al.
PCOM Scholarly Papers
Background: MicroRNAs (miRNAs) are important post-transcriptional regulators which control growth and development in eukaryotes. The cestode Echinococcus granulosus has a complex life-cycle involving different development stages but the mechanisms underpinning this development, including the involvement of miRNAs, remain unknown. Results: Using Illumina next generation sequencing technology, we sequenced at the genome-wide level three small RNA populations from the adult, protoscolex and cyst membrane of E. granulosus. A total of 94 pre-miRNA candidates (coding 91 mature miRNAs and 39 miRNA stars) were in silico predicted. Through comparison of expression profiles, we found 42 mature miRNAs and 23 miRNA stars expressed with …
Egonet: Identification Of Human Disease Ego-Network Modules, Rendong Yang, Yun Bai, Zhaohui Qin, Tianwei Yu
Egonet: Identification Of Human Disease Ego-Network Modules, Rendong Yang, Yun Bai, Zhaohui Qin, Tianwei Yu
PCOM Scholarly Papers
Background: Mining novel biomarkers from gene expression profiles for accurate disease classification is challenging due to small sample size and high noise in gene expression measurements. Several studies have proposed integrated analyses of microarray data and protein-protein interaction (PPI) networks to find diagnostic subnetwork markers. However, the neighborhood relationship among network member genes has not been fully considered by those methods, leaving many potential gene markers unidentified. The main idea of this study is to take full advantage of the biological observation that genes associated with the same or similar diseases commonly reside in the same neighborhood of molecular networks.Results: …
Genome-Wide Expression Analysis In Down Syndrome: Insight Into Immunodeficiency, Chong Li, Lei Jin, Yun Bai, Qimin Chen, Lijun Fu, Minjun Yang, Huasheng Xiao, Guoping Zhao, Shengyue Wang
Genome-Wide Expression Analysis In Down Syndrome: Insight Into Immunodeficiency, Chong Li, Lei Jin, Yun Bai, Qimin Chen, Lijun Fu, Minjun Yang, Huasheng Xiao, Guoping Zhao, Shengyue Wang
PCOM Scholarly Papers
Down syndrome (DS) is caused by triplication of Human chromosome 21 (Hsa21) and associated with an array of deleterious phenotypes, including mental retardation, heart defects and immunodeficiency. Genome-wide expression patterns of uncultured peripheral blood cells are useful to understanding of DS-associated immune dysfunction. We used a Human Exon microarray to characterize gene expression in uncultured peripheral blood cells derived from DS individuals and age-matched controls from two age groups: neonate (N) and child (C). A total of 174 transcript clusters (gene-level) with eight located on Hsa21 in N group and 383 transcript clusters including 56 on Hsa21 in C group …
Capturing Changes In Gene Expression Dynamics By Gene Set Differential Coordination Analysis, Tianwei Yu, Yun Bai
Capturing Changes In Gene Expression Dynamics By Gene Set Differential Coordination Analysis, Tianwei Yu, Yun Bai
PCOM Scholarly Papers
Analyzing gene expression data at the gene set level greatly improves feature extraction and data interpretation. Currently most efforts in gene set analysis are focused on differential expression analysis - finding gene sets whose genes show first-order relationship with the clinical outcome. However the regulation of the biological system is complex, and much of the change in gene expression dynamics do not manifest in the form of differential expression. At the gene set level, capturing the change in expression dynamics is difficult due to the complexity and heterogeneity of the gene sets. Here we report a systematic approach to detect …
Improving Gene Expression Data Interpretation By Finding Latent Factors That Co-Regulate Gene Modules With Clinical Factors, Tianwei Yu, Yun Bai
Improving Gene Expression Data Interpretation By Finding Latent Factors That Co-Regulate Gene Modules With Clinical Factors, Tianwei Yu, Yun Bai
PCOM Scholarly Papers
Background: In the analysis of high-throughput data with a clinical outcome, researchers mostly focus on genes/proteins that show first-order relations with the clinical outcome. While this approach yields biomarkers and biological mechanisms that are easily interpretable, it may miss information that is important to the understanding of disease mechanism and/or treatment response. Here we test the hypothesis that unobserved factors can be mobilized by the living system to coordinate the response to the clinical factors.Results: We developed a computational method named Guided Latent Factor Discovery (GLFD) to identify hidden factors that act in combination with the observed clinical factors to …