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Systems Biology Approaches to Mining High Throughput Biological Data BioMed Research International Systems Biology Approaches to Mining High Throughput Biological Data Guest Editors: Fang-Xiang Wu, Min Li, Jishou Ruan, and Feng Luo Systems Biology Approaches to Mining High Throughput Biological Data BioMed Research International Systems Biology Approaches to Mining High Throughput Biological Data Guest Editors: Fang-Xiang Wu, Min Li, Jishou Ruan, and Feng Luo Copyright © 2015 Hindawi Publishing Corporation. All rights reserved. This is a special issue published in “BioMed Research International.” All articles are open access articles distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Contents Systems Biology Approaches to Mining High Throughput Biological Data, Fang-Xiang Wu, Min Li, Jishou Ruan, and Feng Luo Volume 2015, Article ID 504362, 2 pages ProSim: A Method for Prioritizing Disease Genes Based on Protein Proximity and Disease Similarity, Gamage Upeksha Ganegoda, Yu Sheng, and Jianxin Wang Volume 2015, Article ID 213750, 11 pages Differential Expression Analysis in RNA-Seq by a Naive Bayes Classifier with Local Normalization, YongchaoDou,XiaomeiGuo,LinglingYuan,DavidR.Holding,andChiZhang Volume 2015, Article ID 789516, 9 pages ?? -Profiles: A Nonlinear Clustering Method for Pattern Detection in High Dimensional, Data Kai Wang, Qing Zhao, Jianwei Lu, and Tianwei Yu Volume 2015, Article ID 918954, 10 pages Screening Ingredients from Herbs against Pregnane X Receptor in the Study of Inductive Herb-Drug Interactions: Combining Pharmacophore and Docking-Based Rank Aggregation,ZhijieCui, Hong Kang, Kailin Tang, Qi Liu, Zhiwei Cao, and Ruixin Zhu Volume 2015, Article ID 657159, 8 pages Gene Signature of Human Oral Mucosa Fibroblasts: Comparison with Dermal Fibroblasts and Induced Pluripotent Stem Cells, Keiko Miyoshi, Taigo Horiguchi, Ayako Tanimura, Hiroko Hagita, and Takafumi Noma Volume 2015, Article ID 121575, 19 pages Improving the Mapping of Smith-Waterman Sequence Database Searches onto CUDA-Enabled GPUs, Liang-TsungHuang,Chao-ChinWu,Lien-FuLai,andYun-JuLi Volume 2015, Article ID 185179, 10 pages Similarities in Gene Expression Profiles during In Vitro Aging of Primary Human Embryonic Lung and Foreskin Fibroblasts, Shiva Marthandan, Steffen Priebe, Mario Baumgart, Marco Groth, Alessandro Cellerino, Reinhard Guthke, Peter Hemmerich, and Stephan Diekmann Volume 2015, Article ID 731938, 17 pages Module Based Differential Coexpression Analysis Method for Type 2 Diabetes,LinYuan, Chun-Hou Zheng, Jun-Feng Xia, and De-Shuang Huang Volume 2015, Article ID 836929, 8 pages AcconPred: Predicting Solvent Accessibility and Contact Number Simultaneously by a Multitask Learning Framework under the Conditional Neural Fields Model, Jianzhu Ma and Sheng Wang Volume 2015, Article ID 678764, 10 pages Improving Classification of Protein Interaction Articles Using Context Similarity-Based Feature Selection, Yifei Chen, Yuxing Sun, and Bing-Qing Han Volume 2015, Article ID 751646, 10 pages Spatially Enhanced Differential RNA Methylation Analysis from Affinity-Based Sequencing Data with Hidden Markov Model, Yu-Chen Zhang, Shao-Wu Zhang, Lian Liu, Hui Liu, Lin Zhang, Xiaodong Cui, Yufei Huang, and Jia Meng Volume 2015, Article ID 852070, 12 pages Hindawi Publishing Corporation BioMed Research International Volume 2015, Article ID 504362, 2 pages http://dx.doi.org/10.1155/2015/504362 Editorial Systems Biology Approaches to Mining High Throughput Biological Data Fang-Xiang Wu,1,2 Min Li,3 Jishou Ruan,1 and Feng Luo4 1 School of Mathematical Sciences, Nankai University, Tianjin 300071, China 2Division of Biomedical Engineering, University of Saskatchewan, Saskatoon, SK, Canada S7N 5A9 3School of Information Science and Engineering, Central South University, Changsha 410083, China 4School of Computing, Clemson University, Clemson, SC 29634, USA Correspondence should be addressed to Fang-Xiang Wu; [email protected] Received 8 July 2015; Accepted 8 July 2015 Copyright © 2015 Fang-Xiang Wu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. With advances in high throughput measurement techniques, K-profiles clustering method, which can be seen as the large-scale biological data have been and will continuously nonlinear counterpart of the K-means clustering algorithm. be produced, for example, gene expression data, protein- The method had a built-in statistical testing procedure that protein interaction (PPI) data, tandem mass spectra data, ensures genes not belonging to any cluster do not impact the microRNA expression data, lncRNA expression data, and estimation of cluster profiles. Results from extensive simula- biomolecule-disease association data. Such data contain tion studies showed that K-profiles clustering outperformed insightful information for understanding the mechanism traditional linear K-means algorithm. In addition, K-profile of molecular biological systems and have proved useful in clustering generated biologically meaningful results from a diagnosis, treatment, and drug design for genetic disorders gene expression dataset. or complex diseases. For this focus issue, we have invited Replicative senescence is of fundamental importance for the researchers to contribute original research articles which the process of cellular aging. In the paper “Similarities in develop or improve systems biology approaches to mining Gene Expression Profiles during In Vitro Aging of Primary high throughput biological data. HumanEmbryonicLungandForeskinFibroblasts,”S.Diek- With high throughput data, it is appealing to develop mann et al. elucidated cellular aging process by comparing systems biology approaches to understand important biolog- gene expression changes, measured by RNA-Seq, in fibrob- ical processes. In the paper “Differential Expression Anal- lasts originating from two different tissues, embryonic lung ysis in RNA-Seq by a Naive Bayes Classifier with Local (MRC-5) and foreskin (HFF), at five different time points Normalization,” Y. Dou et al. developed a new tool for the during their transition into senescence. Their results showed identification of differentially expressed genes with RNA- that a number of monotonically up- and downregulated genes Seq data, named GExposer. This tool introduced a local had a novel strong functional link to aging and senescence normalization algorithm to reduce the bias of nonran- related processes. domly positioned read depth. The Naive Bayes classifier was More and more studies have shown that many complex employed to integrate fold change, transcript length, and GC- diseases are contributed jointly by alterations of numerous content to identify differentially expressed genes. Results on genes. Genes often coordinate together as a functional bio- several independent tests showed that GExposer had better logical pathway or network and are highly correlated. In performance than other methods. In the paper “K-Profiles: A the paper “Module Based Differential Coexpression Analysis Nonlinear Clustering Method for Pattern Detection in High Method for Type 2 Diabetes,” L. Yuan et al. proposed a gene Dimensional Data,” K. Wang et al. designed the nonlinear differential coexpression analysis algorithm and applied it to 2 BioMed Research International a publicly available type 2 diabetes (T2D) expression dataset. Protein interaction article classification is a text classi- Two differential coexpression gene modules about T2D were fication task in the biological domain to determine which detected and were expected to be useful for exploring the articles describe protein-protein interactions. In the paper biological functions of the related genes. “Improving Classification of Protein Interaction Articles Oral mucosa is a useful material for regeneration ther- Using Context Similarity-Based Feature Selection,” Y. Chen apy with the advantages of its accessibility and versatility et al. proposed new context similarity-based feature selection regardless of age and gender. In the paper “Gene Signature of methods. Their performances were evaluated on two protein Human Oral Mucosa Fibroblasts: Comparison with Dermal interaction article collections and compared against the Fibroblasts and Induced Pluripotent Stem Cells,” K. Miyoshi frequency-based methods. The experimental results revealed et al. reported the comparative profiles of the gene signatures that the context similarity-based methods performed better of human oral mucosa fibroblasts (hOFs), human dermal in terms of the F1 measure and the dimension reduction rate. fibroblasts (hDFs), and hOF-derived induced pluripotent Recent studies suggest that posttranscriptional RNA stem cells (hOF-iPSCs), linking these with biological roles by modifications play a crucial role in regulating gene expres- functional annotation and pathway analyses. Their findings sion. In practice, a single methylation site can contain demonstrated that hOFs had unique cellular characteristics multiple RNA methylation residuals, some of which can in specificity and plasticity. These data may provide useful be regulated by different enzymes and thus differentially insight into application of oral fibroblasts for direct repro- methylated between two conditions. However, existing peak- graming. based methods could not effectively differentiate multiple Predicting
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