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Network protein function prediction

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https://www.readbyqxmd.com/read/28549478/gladiator-a-global-approach-for-elucidating-disease-modules
#1
Yael Silberberg, Martin Kupiec, Roded Sharan
BACKGROUND: Understanding the genetic basis of disease is an important challenge in biology and medicine. The observation that disease-related proteins often interact with one another has motivated numerous network-based approaches for deciphering disease mechanisms. In particular, protein-protein interaction networks were successfully used to illuminate disease modules, i.e., interacting proteins working in concert to drive a disease. The identification of these modules can further our understanding of disease mechanisms...
May 26, 2017: Genome Medicine
https://www.readbyqxmd.com/read/28546992/identification-of-transcription-factors-potentially-involved-in-human-adipogenesis-in%C3%A2-vitro
#2
Melvin Anyasi Ambele, Michael Sean Pepper
BACKGROUND: Increased adiposity in humans leads to obesity, which is a major risk factor for cardiovascular disease, type 2 diabetes, and cancer. We previously conducted an extensive unbiased in vitro transcriptomic analysis of adipogenesis, using human adipose-derived stromal cells (ASCs). Here, we have applied computational methods to these data to identify transcription factors (TFs) that constitute the upstream gene regulatory networks potentially, driving adipocyte formation in human ASCs...
May 2017: Molecular Genetics & Genomic Medicine
https://www.readbyqxmd.com/read/28545395/characterizing-the-roles-of-changing-population-size-and-selection-on-the-evolution-of-flux-control-in-metabolic-pathways
#3
Alena Orlenko, Peter B Chi, David A Liberles
BACKGROUND: Understanding the genotype-phenotype map is fundamental to our understanding of genomes. Genes do not function independently, but rather as part of networks or pathways. In the case of metabolic pathways, flux through the pathway is an important next layer of biological organization up from the individual gene or protein. Flux control in metabolic pathways, reflecting the importance of mutation to individual enzyme genes, may be evolutionarily variable due to the role of mutation-selection-drift balance...
May 25, 2017: BMC Evolutionary Biology
https://www.readbyqxmd.com/read/28545124/cornet-assigning-function-to-networks-of-co-evolving-residues-by-automated-literature-mining
#4
Tom van den Bergh, Giorgio Tamo, Alberto Nobili, Yifeng Tao, Tianwei Tan, Uwe T Bornscheuer, Remko K P Kuipers, Bas Vroling, René M de Jong, Kalyanasundaram Subramanian, Peter J Schaap, Tom Desmet, Bernd Nidetzky, Gert Vriend, Henk-Jan Joosten
CorNet is a web-based tool for the analysis of co-evolving residue positions in protein super-family sequence alignments. CorNet projects external information such as mutation data extracted from literature on interactively displayed groups of co-evolving residue positions to shed light on the functions associated with these groups and the residues in them. We used CorNet to analyse six enzyme super-families and found that groups of strongly co-evolving residues tend to consist of residues involved in a same function such as activity, specificity, co-factor binding, or enantioselectivity...
2017: PloS One
https://www.readbyqxmd.com/read/28541224/protein-protein-interaction-interface-residue-pair-prediction-based-on-deep-learning-architecture
#5
Zhenni Zhao, Xinqi Gong
MOTIVATION: Proteins usually fulfill their biological functions by interacting with other proteins. Although some methods have been developed to predict the binding sites of a monomer protein, these are not sufficient for prediction of the interaction between two monomer proteins. The correct prediction of interface residue pairs from two monomer proteins is still an open question and has great significance for practical experimental applications in the life sciences. We hope to build a method for the prediction of interface residue pairs that is suitable for those applications...
May 19, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28537507/electroacupuncture-alleviated-brain-damages-through-mir-191a-5p-targeting-neuronal-calcium-sensor-1-after-ischemic-stroke
#6
Heng Zhou, Ceng Yang, Fuhai Bai, Zhi Ma, Jingyi Wang, Feng Wang, Feng Li, Qiang Wang, Lize Xiong
Electroacupuncture (EA) administration before or after cerebral ischemia has been shown to afford protection against ischemic injury. However, the underlying mechanism of EA-mediated protection is still unclear. Functional microRNAs (miRNAs) are believed to play important roles in neuroprotection and synaptic plasticity during and after ischemia. In a previous study, we identified 20 miRNAs that are expressed in the penumbra and are significantly changed after EA treatment. Here, we used bioinformatics analysis to predict the biological functions and gene-networks of these miRNAs...
May 24, 2017: Rejuvenation Research
https://www.readbyqxmd.com/read/28534780/katzlgo-large-scale-prediction-of-lncrna-functions-by-using-the-katz-measure-based-on-multiple-networks
#7
Zuping Zhang, Jingpu Zhang, Chao Fan, Yongjun Tang, Lei Deng
Aggregating evidences have shown that long non-coding RNAs (lncRNAs) generally play key roles in cellular biological processes such as epigenetic regulation, gene expression regulation at transcriptional and post-transcriptional levels, cell differentiation and others. However, most lncRNAs have not been functionally characterized. There is an urgent need to develop computational approaches for function annotation of increasing available lncRNAs. In this article, we propose a global network-based method, KATZLGO, to predict the functions of human lncRNAs at large scale...
May 16, 2017: IEEE/ACM Transactions on Computational Biology and Bioinformatics
https://www.readbyqxmd.com/read/28530547/application-of-machine-learning-approaches-for-protein-protein-interactions-prediction
#8
Mengying Zhang, Qiang Su, Yi Lu, Manman Zhao, Bing Niu
BACKGROUND: Proteomics endeavors to study the structures, functions and interactions of proteins. Information of the protein-protein interactions (PPIs) helps to improve our knowledge of the functions and the 3D structures of proteins. Thus determining the PPIs is essential for the study of the proteomics. OBJECTIVE: In this review, in order to study the application of machine learning in predicting PPI, some machine learning approaches such as support vector machine (SVM), artificial neural networks (ANNs) and random forest (RF) were selected, and the examples of its applications in PPIs were listed...
May 22, 2017: Medicinal Chemistry
https://www.readbyqxmd.com/read/28524240/potential-serum-biomarkers-associated-with-mild-and-severe-leptospirosis-infection-a-cohort-study-in-the-malaysian-population
#9
Tan Xue Ting, Fairuz Binti Amran, Ravindran Thayan, Norazah Ahmad, Roslinda Jaafar, Rahimah Haron, Rafidah Abdullah, Sazwan Reezal Bin Shamsuddin, Nor Suhaila Binti Md Riffin, Puteri Shafinaz Abdul-Rahman
Leptospirosis is an emerging zoonotic infectious disease in Malaysia. The symptoms of leptospirosis vary from mild non-specific flu-like illness to a severe condition which is usually associated with serious complication and fatality. To study the protein expression profile of mild and severe leptospirosis, fifteen paired sera were collected from the patients who were mildly infected and following that progressed to severe stage. The proteome profiles of mild and severe cases were studied using 2DE analysis in combination with LC-MS/MS...
May 19, 2017: Electrophoresis
https://www.readbyqxmd.com/read/28524201/a-computational-framework-for-distinguishing-direct-versus-indirect-interactions-in-human-functional-protein-protein-interaction-networks
#10
Suyu Mei, Erik K Flemington, Kun Zhang
Recognition of indirect interactions is instrumental to in silico reconstruction of signaling pathways and sheds light on the exploration of unknown physical paths between two indirectly interacting genes. However, very limited computational methods have explicitly exploited the indirect interactions with experimental evidence thus far. In this work, we attempt to distinguish direct versus indirect interactions in human functional protein-protein interaction (PPI) networks via a predictive l2-regularized logistic regression model built on the experimental data...
May 19, 2017: Integrative Biology: Quantitative Biosciences From Nano to Macro
https://www.readbyqxmd.com/read/28521415/bioinformatics-analysis-of-dysregulated-micrornas-in-the-nipple-discharge-of-patients-with-breast-cancer
#11
Kai Zhang, Ya-Wen Wang, Rong Ma
MicroRNAs (miRNAs/miRs) have been reported to be associated with the tumorigenesis and progression of various types of human cancer; however, the underlying mechanisms of this association remain unclear. The aim of the present study was to explore the potential functions of miRNAs in the development of breast cancer using bioinformatics analysis, based on the miRNA expression profile in nipple discharge. A previous study demonstrated the upregulation of miR-3646 and miR-4484, and the downregulation of miR-4732-5p in the nipple discharge of patients with breast cancer, compared with patients with benign breast lesions...
May 2017: Oncology Letters
https://www.readbyqxmd.com/read/28515341/bet-bromodomain-inhibition-suppresses-innate-inflammatory-and-profibrotic-transcriptional-networks-in-heart-failure
#12
Qiming Duan, Sarah McMahon, Priti Anand, Hirsh Shah, Sean Thomas, Hazel T Salunga, Yu Huang, Rongli Zhang, Aarathi Sahadevan, Madeleine E Lemieux, Jonathan D Brown, Deepak Srivastava, James E Bradner, Timothy A McKinsey, Saptarsi M Haldar
Despite current standard of care, the average 5-year mortality after an initial diagnosis of heart failure (HF) is about 40%, reflecting an urgent need for new therapeutic approaches. Previous studies demonstrated that the epigenetic reader protein bromodomain-containing protein 4 (BRD4), an emerging therapeutic target in cancer, functions as a critical coactivator of pathologic gene transactivation during cardiomyocyte hypertrophy. However, the therapeutic relevance of these findings to human disease remained unknown...
May 17, 2017: Science Translational Medicine
https://www.readbyqxmd.com/read/28515050/the-mapping-of-predicted-triplex-dna-rna-in-the-drosophila-genome-reveals-a-prominent-location-in-development-and-morphogenesis-related-genes
#13
Claude Pasquier, Sandra Agnel, Alain Robichon
Double-stranded DNA is able to form triple-helical structures by accommodating a third nucleotide strand. A nucleic acid triplex occurs according to Hoogsteen rules that predict the stability and affinity of the third strand bound to the Watson-Crick duplex. The "triplex-forming oligonucleotide" (TFO) can be a short sequence of RNA that binds to the major groove of the targeted duplex only when this duplex presents a sequence of purine or pyrimidine bases in one of the DNA strands. Many nuclear proteins are known to bind triplex DNA or DNA:RNA, but their biological functions are unexplored...
May 17, 2017: G3: Genes—Genomes—Genetics
https://www.readbyqxmd.com/read/28508547/functional-phosphatome-requirement-for-protein-homeostasis-networked-mitochondria-and-sarcomere-structure-in-c-%C3%A2-elegans-muscle
#14
Susann Lehmann, Joseph J Bass, Thomas F Barratt, Mohammed Z Ali, Nathaniel J Szewczyk
BACKGROUND: Skeletal muscle is central to locomotion and metabolic homeostasis. The laboratory worm Caenorhabditis elegans has been developed into a genomic model for assessing the genes and signals that regulate muscle development and protein degradation. Past work has identified a receptor tyrosine kinase signalling network that combinatorially controls autophagy, nerve signal to muscle to oppose proteasome-based degradation, and extracellular matrix-based signals that control calpain and caspase activation...
May 15, 2017: Journal of Cachexia, Sarcopenia and Muscle
https://www.readbyqxmd.com/read/28502001/clustering-and-network-analysis-of-reverse-phase-protein-array-data
#15
Adam Byron
Molecular profiling of proteins and phosphoproteins using a reverse phase protein array (RPPA) platform, with a panel of target-specific antibodies, enables the parallel, quantitative proteomic analysis of many biological samples in a microarray format. Hence, RPPA analysis can generate a high volume of multidimensional data that must be effectively interrogated and interpreted. A range of computational techniques for data mining can be applied to detect and explore data structure and to form functional predictions from large datasets...
2017: Methods in Molecular Biology
https://www.readbyqxmd.com/read/28499419/across-proteome-modeling-of-dimer-structures-for-the-bottom-up-assembly-of-protein-protein-interaction-networks
#16
Surabhi Maheshwari, Michal Brylinski
BACKGROUND: Deciphering complete networks of interactions between proteins is the key to comprehend cellular regulatory mechanisms. A significant effort has been devoted to expanding the coverage of the proteome-wide interaction space at molecular level. Although a growing body of research shows that protein docking can, in principle, be used to predict biologically relevant interactions, the accuracy of the across-proteome identification of interacting partners and the selection of near-native complex structures still need to be improved...
May 12, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28499347/the-dynamics-of-early-state-transcriptional-changes-and-aggregate-formation-in-a-huntington-s-disease-cell-model
#17
Martijn van Hagen, Diewertje G E Piebes, Wim C de Leeuw, Ilona M Vuist, Willeke M C van Roon-Mom, Perry D Moerland, Pernette J Verschure
BACKGROUND: Huntington's disease (HD) is a fatal neurodegenerative disorder caused by a CAG expansion in the Huntingtin (HTT) gene. Proteolytic cleavage of mutant huntingtin (Htt) protein with an expanded polyglutamine (polyQ) stretch results in production of Htt fragments that aggregate and induce impaired ubiquitin proteasome, mitochondrial functioning and transcriptional dysregulation. To understand the time-resolved relationship between aggregate formation and transcriptional changes at early disease stages, we performed temporal transcriptome profiling and quantification of aggregate formation in living cells in an inducible HD cell model...
May 12, 2017: BMC Genomics
https://www.readbyqxmd.com/read/28493910/a-new-two-stage-method-for-revealing-missing-parts-of-edges-in-protein-protein-interaction-networks
#18
Wei Zhang, Jia Xu, Yuanyuan Li, Xiufen Zou
With the increasing availability of high-throughput data, various computational methods have recently been developed for understanding the cell through protein-protein interaction (PPI) networks at a systems level. However, due to the incompleteness of the original PPI networks those efforts have been significantly hindered. In this paper, we propose a two stage method to predict underlying links between two originally unlinked protein pairs. First, we measure gene expression and gene functional similarly between unlinked protein pairs on Saccharomyces cerevisiae benchmark network and obtain new constructed networks...
2017: PloS One
https://www.readbyqxmd.com/read/28487941/identification-of-micrornas-associated-with-medullary-thyroid-carcinoma-by-bioinformatics-analyses
#19
Xiangjun Fu, Jugao Fang, Meng Lian, Qi Zhong, Hongzhi Ma, Ling Feng, Ru Wang, Haizhou Wang
The present study aimed to investigate the microRNA (miRNA) profile in human medullary thyroid carcinoma (MTC) tissue. The GSE40807 data profile was downloaded from the Gene Expression Omnibus database. Following preprocessing, differentially expressed microRNAs (DEMs) between MTC and healthy tissues were identified. Based on the obtained DEMs, transcription factor (TF)‑miRNA and miRNA‑target gene regulatory association pairs were predicted. Finally, functional enrichment analysis was performed on target genes of DEMs...
June 2017: Molecular Medicine Reports
https://www.readbyqxmd.com/read/28477207/from-protein-protein-interactions-to-protein-co-expression-networks-a-new-perspective-to-evaluate-large-scale-proteomic-data
#20
REVIEW
Danila Vella, Italo Zoppis, Giancarlo Mauri, Pierluigi Mauri, Dario Di Silvestre
The reductionist approach of dissecting biological systems into their constituents has been successful in the first stage of the molecular biology to elucidate the chemical basis of several biological processes. This knowledge helped biologists to understand the complexity of the biological systems evidencing that most biological functions do not arise from individual molecules; thus, realizing that the emergent properties of the biological systems cannot be explained or be predicted by investigating individual molecules without taking into consideration their relations...
December 2017: EURASIP Journal on Bioinformatics & Systems Biology
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