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https://www.readbyqxmd.com/read/28105201/comparison-of-microrna-expression-profiles-in-k562-cells-derived-microvesicles-and-parental-cells-and-analysis-of-their-roles-in-leukemia
#1
Xiaomei Chen, Wei Xiong, Huiyu Li
Microvesicles (MVs) are 30-1,000-nm extracellular vesicles that are released from a multitude of cell types and perform diverse cellular functions, including intercellular communication, antigen presentation, and transfer of proteins, messenger RNA and microRNA (also known as miR). MicroRNAs have been demonstrated to be aberrantly expressed in leukemia, and the overall microRNA expression profile may differentiate normal blood cells vs. leukemia cells. MVs containing microRNAs may enable intercellular cross-talk in vivo...
December 2016: Oncology Letters
https://www.readbyqxmd.com/read/28097908/common-and-specific-genes-and-peripheral-biomarkers-in-children-and-adults-with-attention-deficit-hyperactivity-disorder
#2
Cristian Bonvicini, Stephen V Faraone, Catia Scassellati
OBJECTIVES: Elucidating the biological mechanisms involved in Attention-deficit/hyperactivity disorder (ADHD) has been challenging. Relatively unexplored is the fact that these mechanisms can differ with age. METHODS: We present an overview on the major differences between children and adults with ADHD, describing several studies from genomics to metabolomics performed in ADHD children and in adults. A systematic search (up until February, 2016) was conducted. RESULTS: From a PRISMA flow-chart, a total of eligibility 350 studies from genomics and metabolomics were found for cADHD and 91 for aADHD...
January 18, 2017: World Journal of Biological Psychiatry
https://www.readbyqxmd.com/read/28093455/genomewide-landscape-of-gene-metabolome-associations-in-escherichia-coli
#3
Tobias Fuhrer, Mattia Zampieri, Daniel C Sévin, Uwe Sauer, Nicola Zamboni
Metabolism is one of the best-understood cellular processes whose network topology of enzymatic reactions is determined by an organism's genome. The influence of genes on metabolite levels, however, remains largely unknown, particularly for the many genes encoding non-enzymatic proteins. Serendipitously, genomewide association studies explore the relationship between genetic variants and metabolite levels, but a comprehensive interaction network has remained elusive even for the simplest single-celled organisms...
January 16, 2017: Molecular Systems Biology
https://www.readbyqxmd.com/read/28087642/stxbp4-drives-tumor-growth-and-is-associated-with-poor-prognosis-through-pdgf-receptor-signaling-in-lung-squamous-cell-carcinoma
#4
Yukihiro Otaka, Susumu Rokudai, Kyoichi Kaira, Michiru Fujieda, Ikuko Horikoshi, Reika Kawabata, Shinji Yoshiyama, Takehiko Yokobori, Yoichi Ohtaki, Kimihiro Shimizu, Tetsunari Oyama, Jun'ichi Tamura, Carol Prives, Masahiko Nishiyama
PURPOSE: Expression of the ΔN isoform of p63 (ΔNp63) is a diagnostic marker highly specific for lung squamous cell carcinoma (SCC). We previously found that Syntaxin Binding Protein 4 (STXBP4) regulates ΔNp63 ubiquitination, suggesting that STXBP4 may also be a SCC biomarker. To address this issue, we investigated the role of STXBP4 expression in SCC biology and the impact of STXBP4 expression on SCC prognosis. EXPERIMENTAL DESIGN: We carried out a clinicopathological analysis of STXBP4 expression in 87 lung SCC patients...
January 13, 2017: Clinical Cancer Research: An Official Journal of the American Association for Cancer Research
https://www.readbyqxmd.com/read/28086860/nicotiana-attenuata-data-hub-nadh-an-integrative-platform-for-exploring-genomic-transcriptomic-and-metabolomic-data-in-wild-tobacco
#5
Thomas Brockmöller, Zhihao Ling, Dapeng Li, Emmanuel Gaquerel, Ian T Baldwin, Shuqing Xu
BACKGROUND: Nicotiana attenuata (coyote tobacco) is an ecological model for studying plant-environment interactions and plant gene function under real-world conditions. During the last decade, large amounts of genomic, transcriptomic and metabolomic data have been generated with this plant which has provided new insights into how native plants interact with herbivores, pollinators and microbes. However, an integrative and open access platform that allows for the efficient mining of these -omics data remained unavailable until now...
January 13, 2017: BMC Genomics
https://www.readbyqxmd.com/read/28086790/rna-sequencing-for-global-gene-expression-associated-with-muscle-growth-in-a-single-male-modern-broiler-line-compared-to-a-foundational-barred-plymouth-rock-chicken-line
#6
Byung-Whi Kong, Nicholas Hudson, Dongwon Seo, Seok Lee, Bhuwan Khatri, Kentu Lassiter, Devin Cook, Alissa Piekarski, Sami Dridi, Nicholas Anthony, Walter Bottje
BACKGROUND: Modern broiler chickens exhibit very rapid growth and high feed efficiency compared to unselected chicken breeds. The improved production efficiency in modern broiler chickens was achieved by the intensive genetic selection for meat production. This study was designed to investigate the genetic alterations accumulated in modern broiler breeder lines during selective breeding conducted over several decades. METHODS: To identify genes important in determining muscle growth and feed efficiency in broilers, RNA sequencing (RNAseq) was conducted with breast muscle in modern pedigree male (PeM) broilers (n = 6 per group), and with an unselected foundation broiler line (Barred Plymouth Rock; BPR)...
January 13, 2017: BMC Genomics
https://www.readbyqxmd.com/read/28074855/mir-218-targets-mecp2-and-inhibits-heroin-seeking-behavior
#7
Biao Yan, Zhaoyang Hu, Wenqing Yao, Qiumin Le, Bo Xu, Xing Liu, Lan Ma
MicroRNAs (miRNAs) are a class of evolutionarily conserved, 18-25 nucleotide non-coding sequences that post-transcriptionally regulate gene expression. Recent studies implicated their roles in the regulation of neuronal functions, such as learning, cognition and memory formation. Here we report that miR-218 inhibits heroin-induced behavioral plasticity. First, network propagation-based method was used to predict candidate miRNAs that played potential key roles in regulating drug addiction-related genes. Microarray screening was also carried out to identify miRNAs responding to chronic heroin administration in the nucleus accumbens (NAc)...
January 11, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28074633/a-computational-interactome-for-prioritizing-genes-associated-with-complex-agronomic-traits-in-rice
#8
Shiwei Liu, Yihui Liu, Jiawei Zhao, Shitao Cai, Hongmei Qian, Kaijing Zuo, Lingxia Zhao, Lida Zhang
Rice is one of the most important staple foods for more than half of the world's population. Many rice traits are quantitative, complex and controlled by multiple interacting genes. Thus, a full understanding of genetic relationships will be critical to systematically identify genes controlling agronomic traits. We developed a genome-wide rice protein-protein interaction network (RicePPINet, http://netbio.sjtu.edu.cn/riceppinet/) using machine-learning with structural relationship and functional information...
January 11, 2017: Plant Journal: for Cell and Molecular Biology
https://www.readbyqxmd.com/read/28068355/a-methodology-for-cancer-therapeutics-by-systems-pharmacology-based-analysis-a-case-study-on-breast-cancer-related-traditional-chinese-medicines
#9
Yan Li, Jinghui Wang, Feng Lin, Yinfeng Yang, Su-Shing Chen
Breast cancer is the most common carcinoma in women. Comprehensive therapy on breast cancer including surgical operation, chemotherapy, radiotherapy, endocrinotherapy, etc. could help, but still has serious side effect and resistance against anticancer drugs. Complementary and alternative medicine (CAM) may avoid these problems, in which traditional Chinese medicine (TCM) has been highlighted. In this section, to analyze the mechanism through which TCM act on breast cancer, we have built a virtual model consisting of the construction of database, oral bioavailability prediction, drug-likeness evaluation, target prediction, network construction...
2017: PloS One
https://www.readbyqxmd.com/read/28056090/accurate-de-novo-prediction-of-protein-contact-map-by-ultra-deep-learning-model
#10
Sheng Wang, Siqi Sun, Zhen Li, Renyu Zhang, Jinbo Xu
MOTIVATION: Protein contacts contain key information for the understanding of protein structure and function and thus, contact prediction from sequence is an important problem. Recently exciting progress has been made on this problem, but the predicted contacts for proteins without many sequence homologs is still of low quality and not very useful for de novo structure prediction. METHOD: This paper presents a new deep learning method that predicts contacts by integrating both evolutionary coupling (EC) and sequence conservation information through an ultra-deep neural network formed by two deep residual neural networks...
January 2017: PLoS Computational Biology
https://www.readbyqxmd.com/read/28049415/improving-protein-complex-prediction-by-reconstructing-a-high-confidence-protein-protein-interaction-network-of-escherichia-coli-from-different-physical-interaction-data-sources
#11
Shirin Taghipour, Peyman Zarrineh, Mohammad Ganjtabesh, Abbas Nowzari-Dalini
BACKGROUND: Although different protein-protein physical interaction (PPI) datasets exist for Escherichia coli, no common methodology exists to integrate these datasets and extract reliable modules reflecting the existing biological process and protein complexes. Naïve Bayesian formula is the highly accepted method to integrate different PPI datasets into a single weighted PPI network, but detecting proper weights in such network is still a major problem. RESULTS: In this paper, we proposed a new methodology to integrate various physical PPI datasets into a single weighted PPI network in a way that the detected modules in PPI network exhibit the highest similarity to available functional modules...
January 3, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28041882/lncrna-functional-networks-in-oligodendrocytes-reveal-stage-specific-myelination-control-by-an-lncol1-suz12-complex-in-the-cns
#12
Danyang He, Jincheng Wang, Yulan Lu, Yaqi Deng, Chuntao Zhao, Lingli Xu, Yinhuai Chen, Yueh-Chiang Hu, Wenhao Zhou, Q Richard Lu
Long noncoding RNAs (lncRNAs) are emerging as important regulators of cellular functions, but their roles in oligodendrocyte myelination remain undefined. Through de novo transcriptome reconstruction, we establish dynamic expression profiles of lncRNAs at different stages of oligodendrocyte development and uncover a cohort of stage-specific oligodendrocyte-restricted lncRNAs, including a conserved chromatin-associated lncOL1. Co-expression network analyses further define the association of distinct oligodendrocyte-expressing lncRNA clusters with protein-coding genes and predict lncRNA functions in oligodendrocyte myelination...
January 18, 2017: Neuron
https://www.readbyqxmd.com/read/28040565/structure-prediction-and-network-analysis-of-chitinases-from-the-cape-sundew-drosera-capensis
#13
Megha H Unhelkar, Vy T Duong, Kaosoluchi N Enendu, John E Kelly, Seemal Tahir, Carter T Butts, Rachel W Martin
BACKGROUND: Carnivorous plants possess diverse sets of enzymes with novel functionalities applicable to biotechnology, proteomics, and bioanalytical research. Chitinases constitute an important class of such enzymes, with future applications including human-safe antifungal agents and pesticides. Here, we compare chitinases from the genome of the carnivorous plant Drosera capensis to those from related carnivorous plants and model organisms. METHODS: Using comparative modeling, in silico maturation, and molecular dynamics simulation, we produce models of the mature enzymes in aqueous solution...
December 28, 2016: Biochimica et Biophysica Acta
https://www.readbyqxmd.com/read/28027290/single-cell-based-analysis-highlights-a-surge-in-cell-to-cell-molecular-variability-preceding-irreversible-commitment-in-a-differentiation-process
#14
Angélique Richard, Loïs Boullu, Ulysse Herbach, Arnaud Bonnafoux, Valérie Morin, Elodie Vallin, Anissa Guillemin, Nan Papili Gao, Rudiyanto Gunawan, Jérémie Cosette, Ophélie Arnaud, Jean-Jacques Kupiec, Thibault Espinasse, Sandrine Gonin-Giraud, Olivier Gandrillon
In some recent studies, a view emerged that stochastic dynamics governing the switching of cells from one differentiation state to another could be characterized by a peak in gene expression variability at the point of fate commitment. We have tested this hypothesis at the single-cell level by analyzing primary chicken erythroid progenitors through their differentiation process and measuring the expression of selected genes at six sequential time-points after induction of differentiation. In contrast to population-based expression data, single-cell gene expression data revealed a high cell-to-cell variability, which was masked by averaging...
December 2016: PLoS Biology
https://www.readbyqxmd.com/read/28025995/prediction-of-key-genes-and-mirnas-responsible-for-loss-of-muscle-force-in-patients-during-an-acute-exacerbation-of-chronic-obstructive-pulmonary-disease
#15
Yanhong Duan, Min Zhou, Jian Xiao, Chaomin Wu, Lei Zhou, Feng Zhou, Chunling Du, Yuanlin Song
The present study aimed to identify genes and microRNAs (miRNAs or miRs) that were abnormally expressed in the vastus lateralis muscle of patients with acute exacerbations of chronic obstructive pulmonary disease (AECOPD). The gene expression profile of GSE10828 was downloaded from the Gene Expression Omnibus database, and this dataset was comprised of 4 samples from patients with AECOPD and 5 samples from patients with stable COPD. Differentially expressed genes (DEGs) were screened using the Limma package in R...
November 2016: International Journal of Molecular Medicine
https://www.readbyqxmd.com/read/28024464/a-network-based-systems-biology-platform-for-predicting-disease-metabolite-links
#16
Henri Wathieu, Naiem T Issa, Manisha Mohandoss, Stephen W Byers, Sivanesan Dakshanamurthy
Metabolites constitute phenotypic end products of gene expression, and are key players in biological networks. For this reason, the field of metabolomics has been useful in predicting, explaining, and affecting the mechanisms of disease phenotypes. MSD-MAP (Multi Scale Disease-Metabolite Association Platform) is a powerful computational tool for hypothesizing new links between diseases and metabolites, and characterizing the functional basis of those links in a systems biology context. Upon integrating both predicted and known metabolite-protein associations, MSD-MAP takes a two-pronged approach to associating metabolites to a disease, relying on network-based characterization of disease perturbation at multiple levels of biological activity as well as statistical matching of metabolite- and disease-associated biological profiles...
December 14, 2016: Combinatorial Chemistry & High Throughput Screening
https://www.readbyqxmd.com/read/28018170/mrna-transcriptomics-of-galectins-unveils-heterogeneous-organization-in-mouse-and-human-brain
#17
Sebastian John, Rashmi Mishra
Background: Galectins, a family of non-classically secreted, β-galactoside binding proteins is involved in several brain disorders; however, no systematic knowledge on the normal neuroanatomical distribution and functions of galectins exits. Hence, the major purpose of this study was to understand spatial distribution and predict functions of galectins in brain and also compare the degree of conservation vs. divergence between mouse and human species. The latter objective was required to determine the relevance and appropriateness of studying galectins in mouse brain which may ultimately enable us to extrapolate the findings to human brain physiology and pathologies...
2016: Frontiers in Molecular Neuroscience
https://www.readbyqxmd.com/read/28011771/improving-protein-disorder-prediction-by-deep-bidirectional-long-short-term-memory-recurrent-neural-networks
#18
Jack Hanson, Yuedong Yang, Kuldip Paliwal, Yaoqi Zhou
MOTIVATION: Capturing long-range interactions between structural but not sequence neighbors of proteins is a long-standing challenging problem in bioinformatics. Recently, long short-term memory (LSTM) networks have significantly improved the accuracy of speech and image classification problems by remembering useful past information in long sequential events. Here, we have implemented deep bidirectional LSTM recurrent neural networks in the problem of protein intrinsic disorder prediction...
December 22, 2016: Bioinformatics
https://www.readbyqxmd.com/read/28009266/elucidation-of-signaling-pathways-from-large-scale-phosphoproteomic-data-using-protein-interaction-networks
#19
Jan Daniel Rudolph, Marjo de Graauw, Bob van de Water, Tamar Geiger, Roded Sharan
Phosphoproteomic experiments typically identify sites within a protein that are differentially phosphorylated between two or more cell states. However, the interpretation of these data is hampered by the lack of methods that can translate site-specific information into global maps of active proteins and signaling networks, especially as the phosphoproteome is often undersampled. Here, we describe PHOTON, a method for interpreting phosphorylation data within their signaling context, as captured by protein-protein interaction networks, to identify active proteins and pathways and pinpoint functional phosphosites...
December 21, 2016: Cell Systems
https://www.readbyqxmd.com/read/28007948/genome-metabolite-associations-revealed-low-heritability-high-genetic-complexity-and-causal-relations-for-leaf-metabolites-in-winter-wheat-triticum-aestivum
#20
Andrea Matros, Guozheng Liu, Anja Hartmann, Yong Jiang, Yusheng Zhao, Huange Wang, Erhard Ebmeyer, Viktor Korzun, Ralf Schachschneider, Ebrahim Kazman, Johannes Schacht, Friedrich Longin, Jochen Christoph Reif, Hans-Peter Mock
We investigated associations between the metabolic phenotype, consisting of quantitative data of 76 metabolites from 135 contrasting winter wheat (Triticum aestivum) lines, and 17 372 single nucleotide polymorphism (SNP) markers. Metabolite profiles were generated from flag leaves of plants from three different environments, with average repeatabilities of 0.5-0.6. The average heritability of 0.25 was unaffected by the heading date. Correlations among metabolites reflected their functional grouping, highlighting the strict coordination of various routes of the citric acid cycle...
December 22, 2016: Journal of Experimental Botany
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