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Network gene function prediction

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https://www.readbyqxmd.com/read/28724614/nuclear-mtor-acts-as-a-transcriptional-integrator-of-the-androgen-signaling-pathway-in-prostate-cancer
#1
Étienne Audet-Walsh, Catherine R Dufour, Tracey Yee, Fatima Z Zouanat, Ming Yan, Georges Kalloghlian, Mathieu Vernier, Maxime Caron, Guillaume Bourque, Eleonora Scarlata, Lucie Hamel, Fadi Brimo, Armen G Aprikian, Jacques Lapointe, Simone Chevalier, Vincent Giguère
Androgen receptor (AR) signaling reprograms cellular metabolism to support prostate cancer (PCa) growth and survival. Another key regulator of cellular metabolism is mTOR, a kinase found in diverse protein complexes and cellular localizations, including the nucleus. However, whether nuclear mTOR plays a role in PCa progression and participates in direct transcriptional cross-talk with the AR is unknown. Here, via the intersection of gene expression, genomic, and metabolic studies, we reveal the existence of a nuclear mTOR-AR transcriptional axis integral to the metabolic rewiring of PCa cells...
July 19, 2017: Genes & Development
https://www.readbyqxmd.com/read/28717649/circular-rna-profiling-and-bioinformatic-modeling-identify-its-regulatory-role-in-hepatic-steatosis
#2
Xing-Ya Guo, Chong-Xin He, Yu-Qin Wang, Chao Sun, Guang-Ming Li, Qing Su, Qin Pan, Jian-Gao Fan
Circular RNAs (circRNAs) exhibit a wide range of physiological and pathological activities. To uncover their role in hepatic steatosis, we investigated the expression profile of circRNAs in HepG2-based hepatic steatosis induced by high-fat stimulation. Differentially expressed circRNAs were subjected to validation using QPCR and functional analyses using principal component analysis, hierarchical clustering, target prediction, gene ontology (GO), and pathway annotation, respectively. Bioinformatic integration established the circRNA-miRNA-mRNA regulatory network so as to identify the mechanisms underlying circRNAs' metabolic effect...
2017: BioMed Research International
https://www.readbyqxmd.com/read/28716001/variant-ranker-a-web-tool-to-rank-genomic-data-according-to-functional-significance
#3
John Alexander, Dimitris Mantzaris, Marianthi Georgitsi, Petros Drineas, Peristera Paschou
BACKGROUND: The increasing volume and complexity of high-throughput genomic data make analysis and prioritization of variants difficult for researchers with limited bioinformatics skills. Variant Ranker allows researchers to rank identified variants and determine the most confident variants for experimental validation. RESULTS: We describe Variant Ranker, a user-friendly simple web-based tool for ranking, filtering and annotation of coding and non-coding variants...
July 17, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28715999/factors-affecting-interactome-based-prediction-of-human-genes-associated-with-clinical-signs
#4
Sara González-Pérez, Florencio Pazos, Mónica Chagoyen
BACKGROUND: Clinical signs are a fundamental aspect of human pathologies. While disease diagnosis is problematic or impossible in many cases, signs are easier to perceive and categorize. Clinical signs are increasingly used, together with molecular networks, to prioritize detected variants in clinical genomics pipelines, even if the patient is still undiagnosed. Here we analyze the ability of these network-based methods to predict genes that underlie clinical signs from the human interactome...
July 17, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28715997/an-efficient-algorithm-for-improving-structure-based-prediction-of-transcription-factor-binding-sites
#5
Alvin Farrel, Jun-Tao Guo
BACKGROUND: Gene expression is regulated by transcription factors binding to specific target DNA sites. Understanding how and where transcription factors bind at genome scale represents an essential step toward our understanding of gene regulation networks. Previously we developed a structure-based method for prediction of transcription factor binding sites using an integrative energy function that combines a knowledge-based multibody potential and two atomic energy terms. While the method performs well, it is not computationally efficient due to the exponential increase in the number of binding sequences to be evaluated for longer binding sites...
July 17, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28713998/identification-of-micrornas-in-acute-respiratory-distress-syndrome-based-on-microrna-expression-profile-in-rats
#6
Yinghui Guan, Xiang Jin, Xingang Liu, Yuanping Huang, Man Wang, Xiaodan Li
Acute respiratory distress syndrome (ARDS) remains a severe disease associated with an ~40% mortality rate and as many as 200,000 new cases annually. MicroRNAs (miRNAs) have important roles in gene regulation and cancer development. The present study aimed to identify the potential roles of miRNAs in the pathogenesis and progression of ARDS. The miRNA expression profile of the GSE57223 dataset was downloaded from the Gene Expression Omnibus database. Following data normalization, differentially expressed miRNAs were identified using the t‑test method...
July 12, 2017: Molecular Medicine Reports
https://www.readbyqxmd.com/read/28713985/microarray-expression-profiles-of-long-non-coding-rnas-in-germinal-center-like-diffuse-large-b-cell-lymphoma
#7
Hong-Yu Gao, Bin Wu, Wei Yan, Zi-Mu Gong, Qi Sun, Hui-Han Wang, Wei Yang
Long non-coding RNAs (lncRNAs) are continuously transcribed and are involved in various cellular activities. However, their contributions to the occurrence and development of germinal center B-cell (GCB)-like diffuse large B-cell lymphoma (DLBCL) remain largely unknown. We applied microarray technology to profile the expression of lncRNAs in two different GCB-DLBCL cell lines (OCI-ly1 and OCI-ly19) and normal B lymphocytes. We demonstrated that 21,539 lncRNAs were expressed in all of the samples analyzed...
July 14, 2017: Oncology Reports
https://www.readbyqxmd.com/read/28713977/analysis-of-gene-expression-profile-microarray-data-in-complex-regional-pain-syndrome
#8
Wulin Tan, Yiyan Song, Chengqiang Mo, Shuangjian Jiang, Zhongxing Wang
The aim of the present study was to predict key genes and proteins associated with complex regional pain syndrome (CRPS) using bioinformatics analysis. The gene expression profiling microarray data, GSE47603, which included peripheral blood samples from 4 patients with CRPS and 5 healthy controls, was obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in CRPS patients compared with healthy controls were identified using the GEO2R online tool. Functional enrichment analysis was then performed using The Database for Annotation Visualization and Integrated Discovery online tool...
July 12, 2017: Molecular Medicine Reports
https://www.readbyqxmd.com/read/28713939/microarray-analysis-reveals-key-genes-and-pathways-in-tetralogy-of-fallot
#9
Yue-E He, Hui-Xian Qiu, Jian-Bing Jiang, Rong-Zhou Wu, Ru-Lian Xiang, Yuan-Hai Zhang
The aim of the present study was to identify key genes that may be involved in the pathogenesis of Tetralogy of Fallot (TOF) using bioinformatics methods. The GSE26125 microarray dataset, which includes cardiovascular tissue samples derived from 16 children with TOF and five healthy age‑matched control infants, was downloaded from the Gene Expression Omnibus database. Differential expression analysis was performed between TOF and control samples to identify differentially expressed genes (DEGs) using Student's t‑test, and the R/limma package, with a log2 fold‑change of >2 and a false discovery rate of <0...
July 6, 2017: Molecular Medicine Reports
https://www.readbyqxmd.com/read/28710369/the-adipokine-leptin-modulates-adventitial-pericyte-functions-by-autocrine-and-paracrine-signalling
#10
Federica Riu, Sadie C Slater, Eva Jover Garcia, Iker Rodriguez-Arabaolaza, Valeria Alvino, Elisa Avolio, Giuseppe Mangialardi, Andrea Cordaro, Simon Satchell, Carlo Zebele, Andrea Caporali, Gianni Angelini, Paolo Madeddu
Transplantation of adventitial pericytes (APCs) improves recovery from tissue ischemia in preclinical animal models by still unknown mechanisms. This study investigates the role of the adipokine leptin (LEP) in the regulation of human APC biological functions. Transcriptomic analysis of APCs showed components of the LEP signalling pathway are modulated by hypoxia. Kinetic studies indicate cultured APCs release high amounts of immunoreactive LEP following exposure to hypoxia, continuing upon return to normoxia...
July 14, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28708583/circular-rna-expression-profile-and-potential-function-of-hsa_circrna_101238-in-human-thoracic-aortic-dissection
#11
Meisheng Zou, Chixiong Huang, Xinzhong Li, Xiang He, Yanmei Chen, Wangjun Liao, Yulin Liao, Jie Sun, Ze Liu, Lintao Zhong, Jianping Bin
OBJECTIVE: To assess the circular RNAs (circRNAs) expression profile and explore the potential functions in human thoracic aortic dissection (TAD). METHODS: The differentially expressed circRNAs profiles of the aortic segments between human type A TAD patients (n=3) and age-matched normal donors (NA; n=3) were analyzed using the Arraystar human circRNAs microarray. Quantitative real-time PCR was used to validate the expression pattern of circRNAs, parental genes, and hsa-miR-320a; Western blotting confirmed MMP9 expression with additional samples...
July 5, 2017: Oncotarget
https://www.readbyqxmd.com/read/28704398/temporal-dynamics-of-neurogenomic-plasticity-in-response-to-social-interactions-in-male-threespined-sticklebacks
#12
Syed Abbas Bukhari, Michael C Saul, Christopher H Seward, Huimin Zhang, Miles Bensky, Noelle James, Sihai Dave Zhao, Sriram Chandrasekaran, Lisa Stubbs, Alison M Bell
Animals exhibit dramatic immediate behavioral plasticity in response to social interactions, and brief social interactions can shape the future social landscape. However, the molecular mechanisms contributing to behavioral plasticity are unclear. Here, we show that the genome dynamically responds to social interactions with multiple waves of transcription associated with distinct molecular functions in the brain of male threespined sticklebacks, a species famous for its behavioral repertoire and evolution. Some biological functions (e...
July 2017: PLoS Genetics
https://www.readbyqxmd.com/read/28698868/diagnostic-microrna-biomarker-discovery-for-non-small-cell-lung-cancer-adenocarcinoma-by-integrative-bioinformatics-analysis
#13
Yang Shao, Bin Liang, Fei Long, Shu-Juan Jiang
Lung cancer is the leading cause of cancer death and its incidence is ranked high in men and women worldwide. Non-small-cell lung cancer (NSCLC) adenocarcinoma is one of the most frequent histological subtypes of lung cancer. The aberration profile and the molecular mechanism driving its progression are the key for precision therapy of lung cancer, while the screening of biomarkers is essential to the precision early diagnosis and treatment of the cancer. In this work, we applied a bioinformatics method to analyze the dysregulated interaction network of microRNA-mRNA in NSCLC, based on both the gene expression data and the microRNA-gene regulation network...
2017: BioMed Research International
https://www.readbyqxmd.com/read/28694066/disease-gene-classification-with-metagraph-representations
#14
Sezin Ata Kircali, Yuan Fang, Min Wu, Xiao-Li Li, Xiaokui Xiao
Protein-protein interaction (PPI) networks play an important role in studying the functional roles of proteins, including their association with diseases. However, protein interaction networks are not sufficient without the support of additional biological knowledge for proteins such as their molecular functions and biological processes. To complement and enrich PPI networks, we propose to exploit biological properties of individual proteins. More specifically, we integrate keywords describing protein properties into the PPI network, and construct a novel PPI-Keywords (PPIK) network consisting of both proteins and keywords as two different types of nodes...
July 7, 2017: Methods: a Companion to Methods in Enzymology
https://www.readbyqxmd.com/read/28693226/screening-of-potentially-crucial-genes-and-regulatory-factors-involved-in-epithelial-ovarian-cancer-using-microarray-analysis
#15
Can Shi, Zhenyu Zhang
The present study aimed to screen potential genes implicated in epithelial ovarian cancer (EOC) and to further understand the molecular pathogenesis of EOC. In order to do this, datasets GSE14407 (containing 12 human ovarian cancer epithelia samples and 12 normal epithelia samples) and GSE29220 (containing 11 salivary transcriptomes from ovarian cancer patients with serous papillary adenocarcinoma and 11 matched controls) were obtained from the Gene Expression Omnibus. Differentially expressed genes (DEGs) within these datasets were screened using the Linear Models for Microarray Data package, and potential gene functions were predicted by functional and pathway enrichment analyses...
July 2017: Oncology Letters
https://www.readbyqxmd.com/read/28688561/uncovering-the-pathogenesis-of-microtia-using-bioinformatics-approach
#16
Liu Lei, Liu Zhenzhong, Lin Lin, Pan Bo
OBJECTIVE: Bioinformatics is widely used in the field of cancer research, but in the research of pathogenesis of congenital malformations the situation is different. The aim of this study was to explore the underlying mechanism using bioinformatics approach. METHODS: The data were available from Mouse Genome Informatics and Pubmed. Protein-protein interaction (PPI) network of pathogenic genes was conducted using STRING. Gene ontology and pathway enrichment analyses were also performed to pathogenic genes...
August 2017: International Journal of Pediatric Otorhinolaryngology
https://www.readbyqxmd.com/read/28687755/the-integrated-pathway-of-tgf%C3%AE-snail-with-tnf%C3%AE-nf%C3%AE%C2%BAb-may-facilitate-the-tumor-stroma-interaction-in-the-emt-process-and-colorectal-cancer-prognosis
#17
Hui Li, Anjing Zhong, Si Li, Xianwen Meng, Xue Wang, Fangying Xu, Maode Lai
Substantial evidence has shown that epithelial-mesenchymal transition (EMT) plays critical roles in colorectal cancer (CRC) development and prognosis. To uncover the pivotal regulators that function in the cooperative interactions between cancer cells and their microenvironment and consequently affect the EMT process, we carried out a systematic analysis and evaluated prognosis in CRC specimens. Tumor buds and their surrounding stroma were captured using laser microdissection. We used gene expression profiling, bioinformatics analysis and regulatory network construction for molecular selection...
July 7, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28687067/genome-wide-characterization-of-the-aldehyde-dehydrogenase-gene-superfamily-in-soybean-and-its-potential-role-in-drought-stress-response
#18
Wei Wang, Wei Jiang, Juge Liu, Yang Li, Junyi Gai, Yan Li
BACKGROUND: Aldehyde dehydrogenases (ALDHs) represent a group of enzymes that detoxify aldehydes by facilitating their oxidation to carboxylic acids, and have been shown to play roles in plant response to abiotic stresses. However, the comprehensive analysis of ALDH superfamily in soybean (Glycine max) has been limited. RESULTS: In present study, a total of 53 GmALDHs were identified in soybean, and grouped into 10 ALDH families according to the ALDH Gene Nomenclature Committee and phylogenetic analysis...
July 7, 2017: BMC Genomics
https://www.readbyqxmd.com/read/28685167/medial-temporal-pathways-for-contextual-learning-network-c-fos-mapping-in-rats-with-or-without-perirhinal-cortex-lesions
#19
Lisa Kinnavane, Eman Amin, Cristian M Olarte-Sánchez, John P Aggleton
BACKGROUND: In the rat brain, context information is thought to engage network interactions between the postrhinal cortex, medial entorhinal cortex, and the hippocampus. In contrast, object information is thought to be more reliant on perirhinal cortex and lateral entorhinal cortex interactions with the hippocampus. METHOD: The 'context network' was explored by mapping expression of the immediate-early gene, c-fos, after exposure to a new spatial environment. RESULTS: Structural equation modelling of Fos counts produced networks of good fit that closely matched prior predictions based on anatomically-grounded functional models...
March 14, 2017: Brain and neuroscience advances
https://www.readbyqxmd.com/read/28684341/near-perfect-protein-multi-label-classification-with-deep-neural-networks
#20
Balázs Szalkai, Vince Grolmusz
Biological sequences can be considered as data items of high-, non-fixed dimensions, corresponding to the length of those sequences. The comparison and the classification of biological sequences in their relations to large databases are important areas of research today. Artificial neural networks (ANNs) have gained a well-deserved popularity among machine learning tools upon their recent successful applications in image- and sound processing and classification problems. ANNs have also been applied for predicting the family or function of a protein, knowing its residue sequence...
July 3, 2017: Methods: a Companion to Methods in Enzymology
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