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BMC Systems Biology

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https://www.readbyqxmd.com/read/29145845/network-pharmacological-mechanisms-of-vernonia-anthelmintica-l-in-the-treatment-of-vitiligo-isorhamnetin-induction-of-melanogenesis-via-up-regulation-of-melanin-biosynthetic-genes
#1
Ji Ye Wang, Hong Chen, Yin Yin Wang, Xiao Qin Wang, Han Ying Chen, Mei Zhang, Yun Tang, Bo Zhang
BACKGROUND: Vitiligo is a long-term skin disease characterized by the loss of pigment in the skin. The current therapeutic approaches are limited. Although the anti-vitiligo mechanisms of Vernonia anthelmintica (L.) remain ambiguous, the herb has been broadly used in Uyghur hospitals to treat vitiligo. The overall objective of the present study aims to identify the potential lead compounds from Vernonia anthelmintica (L.) in the treatment of vitiligo via an oral route as well as the melanogenic mechanisms in the systematic approaches in silico of admetSAR and substructure-drug-target network-based inference (SDTNBI)...
November 16, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/29073909/genotype-driven-identification-of-a-molecular-network-predictive-of-advanced-coronary-calcium-in-clinseq%C3%A2-and-framingham-heart-study-cohorts
#2
Cihan Oguz, Shurjo K Sen, Adam R Davis, Yi-Ping Fu, Christopher J O'Donnell, Gary H Gibbons
BACKGROUND: One goal of personalized medicine is leveraging the emerging tools of data science to guide medical decision-making. Achieving this using disparate data sources is most daunting for polygenic traits. To this end, we employed random forests (RFs) and neural networks (NNs) for predictive modeling of coronary artery calcium (CAC), which is an intermediate endo-phenotype of coronary artery disease (CAD). METHODS: Model inputs were derived from advanced cases in the ClinSeq®; discovery cohort (n=16) and the FHS replication cohort (n=36) from 89 (th) -99 (th) CAC score percentile range, and age-matched controls (ClinSeq®; n=16, FHS n=36) with no detectable CAC (all subjects were Caucasian males)...
October 26, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/29029622/paracrine-and-autocrine-regulation-of-gene-expression-by-wnt-inhibitor-dickkopf-in-wild-type-and-mutant-hepatocytes
#3
Niklas Hartung, Uwe Benary, Jana Wolf, Bente Kofahl
BACKGROUND: Cells are able to communicate and coordinate their function within tissues via secreted factors. Aberrant secretion by cancer cells can modulate this intercellular communication, in particular in highly organised tissues such as the liver. Hepatocytes, the major cell type of the liver, secrete Dickkopf (Dkk), which inhibits Wnt/ β-catenin signalling in an autocrine and paracrine manner. Consequently, Dkk modulates the expression of Wnt/ β-catenin target genes. We present a mathematical model that describes the autocrine and paracrine regulation of hepatic gene expression by Dkk under wild-type conditions as well as in the presence of mutant cells...
October 13, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/29020948/informed-walks-whispering-hints-to-gene-hunters-inside-networks-jungle
#4
Marilena M Bourdakou, George M Spyrou
BACKGROUND: Systemic approaches offer a different point of view on the analysis of several types of molecular associations as well as on the identification of specific gene communities in several cancer types. However, due to lack of sufficient data needed to construct networks based on experimental evidence, statistical gene co-expression networks are widely used instead. Many efforts have been made to exploit the information hidden in these networks. However, these approaches still need to capitalize comprehensively the prior knowledge encrypted into molecular pathway associations and improve their efficiency regarding the discovery of both exclusive subnetworks as candidate biomarkers and conserved subnetworks that may uncover common origins of several cancer types...
October 11, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/29017547/reconstructing-cancer-drug-response-networks-using-multitask-learning
#5
Matthew Ruffalo, Petar Stojanov, Venkata Krishna Pillutla, Rohan Varma, Ziv Bar-Joseph
BACKGROUND: Translating in vitro results to clinical tests is a major challenge in systems biology. Here we present a new Multi-Task learning framework which integrates thousands of cell line expression experiments to reconstruct drug specific response networks in cancer. RESULTS: The reconstructed networks correctly identify several shared key proteins and pathways while simultaneously highlighting many cell type specific proteins. We used top proteins from each drug network to predict survival for patients prescribed the drug...
October 10, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/29017496/a-novel-interaction-perturbation-analysis-reveals-a-comprehensive-regulatory-principle-underlying-various-biochemical-oscillators
#6
Jun Hyuk Kang, Kwang-Hyun Cho
BACKGROUND: Biochemical oscillations play an important role in maintaining physiological and cellular homeostasis in biological systems. The frequency and amplitude of oscillations are regulated to properly adapt to environments by numerous interactions within biomolecular networks. Despite the advances in our understanding of biochemical oscillators, the relationship between the network structure of an oscillator and its regulatory function still remains unclear. To investigate such a relationship in a systematic way, we have developed a novel analysis method called interaction perturbation analysis that enables direct modulation of the strength of every interaction and evaluates its consequence on the regulatory function...
October 10, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28984210/a-systematic-analysis-of-fda-approved-anticancer-drugs
#7
Jingchun Sun, Qiang Wei, Yubo Zhou, Jingqi Wang, Qi Liu, Hua Xu
BACKGROUND: The discovery of novel anticancer drugs is critical for the pharmaceutical research and development, and patient treatment. Repurposing existing drugs that may have unanticipated effects as potential candidates is one way to meet this important goal. Systematic investigation of efficient anticancer drugs could provide valuable insights into trends in the discovery of anticancer drugs, which may contribute to the systematic discovery of new anticancer drugs. RESULTS: In this study, we collected and analyzed 150 anticancer drugs approved by the US Food and Drug Administration (FDA)...
October 3, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28984203/system-modeling-reveals-the-molecular-mechanisms-of-hsc-cell-cycle-alteration-mediated-by-maff-and-egr3-under-leukemia
#8
Rudong Li, Yin Wang, Hui Cheng, Gang Liu, Tao Cheng, Yunlong Liu, Lei Liu
BACKGROUND: Molecular mechanisms of the functional alteration of hematopoietic stem cells (HSCs) in leukemic environment attract intensive research interests. As known in previous researches, Maff and Egr3 are two important genes having opposite functions on cell cycle; however, they are both highly expressed in HSCs under leukemia. Hence, exploring the molecular mechanisms of how the genes act on cell cycle will help revealing the functional alteration of HSCs. RESULTS: We herein utilize the bioinformatic resources to computationally model the acting mechanisms of Maff and Egr3 on cell cycle...
October 3, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28984200/incorporating-genomic-transcriptomic-and-clinical-data-a-prognostic-and-stem-cell-like-myc-and-prc-imbalance-in-high-risk-neuroblastoma
#9
Xinan Holly Yang, Fangming Tang, Jisu Shin, John M Cunningham
BACKGROUND: Previous studies suggested that cancer cells possess traits reminiscent of the biological mechanisms ascribed to normal embryonic stem cells (ESCs) regulated by MYC and Polycomb repressive complex 2 (PRC2). Several poorly differentiated adult tumors showed preferentially high expression levels in targets of MYC, coincident with low expression levels in targets of PRC2. This paper will reveal this ESC-like cancer signature in high-risk neuroblastoma (HR-NB), the most common extracranial solid tumor in children...
October 3, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28984199/roles-of-alternative-splicing-in-modulating-transcriptional-regulation
#10
Jin Li, Yang Wang, Xi Rao, Yue Wang, Weixing Feng, Hong Liang, Yunlong Liu
BACKGROUND: The ability of a transcription factor to regulate its targets is modulated by a variety of genetic and epigenetic mechanisms. Alternative splicing can modulate gene function by adding or removing certain protein domains, and therefore affect the activity of protein. Reverse engineering of gene regulatory networks using gene expression profiles has proven valuable in dissecting the logical relationships among multiple proteins during the transcriptional regulation. However, it is unclear whether alternative splicing of certain proteins affects the activity of other transcription factors...
October 3, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28984196/multitype-bellman-harris-branching-model-provides-biological-predictors-of-early-stages-of-adult-hippocampal-neurogenesis
#11
Biao Li, Amanda Sierra, Juan Jose Deudero, Fatih Semerci, Andrew Laitman, Marek Kimmel, Mirjana Maletic-Savatic
BACKGROUND: Adult hippocampal neurogenesis, the process of formation of new neurons, occurs throughout life in the hippocampus. New neurons have been associated with learning and memory as well as mood control, and impaired neurogenesis has been linked to depression, schizophrenia, autism and cognitive decline during aging. Thus, understanding the biological properties of adult neurogenesis has important implications for human health. Computational models of neurogenesis have attempted to derive biologically relevant knowledge, hard to achieve using experimentation...
October 3, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28984195/md-miner-a-network-based-approach-for-personalized-drug-repositioning
#12
Haoyang Wu, Elise Miller, Denethi Wijegunawardana, Kelly Regan, Philip R O Payne, Fuhai Li
BACKGROUND: Due to advances in next generation sequencing technologies and corresponding reductions in cost, it is now attainable to investigate genome-wide gene expression and variants at a patient-level, so as to better understand and anticipate heterogeneous responses to therapy. Consequently, it is feasible to inform personalized drug treatment decisions using personal genomics data. However, these efforts are limited due to a lack of reliable computational approaches for predicting effective drugs for individual patients...
October 3, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28984194/the-international-conference-on-intelligent-biology-and-medicine-icibm-2016-putting-systems-biology-to-work
#13
EDITORIAL
W Jim Zheng, Jianhua Ruan, Hua Xu, Zhongming Zhao, Zhangdong Liu
Between December 8-10, 2016, the International Conference on Intelligent Biology and Medicine (ICIBM 2016) was held in Houston, Texas, USA. The conference included eight scientific sessions, four tutorials, one poster session, four highlighted talks and four keynotes that covered topics in 3D genome structure analysis and visualization, next generation sequencing analysis, computational drug discovery, medical informatics, cancer genomics and systems biology. Systems biology has been a main theme in ICIBM 2016, with exciting advances were presented in many areas of systems biology...
October 3, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28984192/a-link-prediction-approach-to-cancer-drug-sensitivity-prediction
#14
Turki Turki, Zhi Wei
BACKGROUND: Predicting the response to a drug for cancer disease patients based on genomic information is an important problem in modern clinical oncology. This problem occurs in part because many available drug sensitivity prediction algorithms do not consider better quality cancer cell lines and the adoption of new feature representations; both lead to the accurate prediction of drug responses. By predicting accurate drug responses to cancer, oncologists gain a more complete understanding of the effective treatments for each patient, which is a core goal in precision medicine...
October 3, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28950906/mimvec-a-deep-learning-approach-for-analyzing-the-human-phenome
#15
Mingxin Gan, Wenran Li, Wanwen Zeng, Xiaojian Wang, Rui Jiang
BACKGROUND: The human phenome has been widely used with a variety of genomic data sources in the inference of disease genes. However, most existing methods thus far derive phenotype similarity based on the analysis of biomedical databases by using the traditional term frequency-inverse document frequency (TF-IDF) formulation. This framework, though intuitive, not only ignores semantic relationships between words but also tends to produce high-dimensional vectors, and hence lacks the ability to precisely capture intrinsic semantic characteristics of biomedical documents...
September 21, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28950905/hybrid-method-to-solve-hp-model-on-3d-lattice-and-to-probe-protein-stability-upon-amino-acid-mutations
#16
Yuzhen Guo, Fengying Tao, Zikai Wu, Yong Wang
BACKGROUND: Predicting protein structure from amino acid sequence is a prominent problem in computational biology. The long range interactions (or non-local interactions) are known as the main source of complexity for protein folding and dynamics and play the dominant role in the compact architecture. Some simple but exact model, such as HP model, captures the pain point for this difficult problem and has important implications to understand the mapping between protein sequence and structure...
September 21, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28950903/bayesian-network-model-for-identification-of-pathways-by-integrating-protein-interaction-with-genetic-interaction-data
#17
Changhe Fu, Su Deng, Guangxu Jin, Xinxin Wang, Zu-Guo Yu
BACKGROUND: Molecular interaction data at proteomic and genetic levels provide physical and functional insights into a molecular biosystem and are helpful for the construction of pathway structures complementarily. Despite advances in inferring biological pathways using genetic interaction data, there still exists weakness in developed models, such as, activity pathway networks (APN), when integrating the data from proteomic and genetic levels. It is necessary to develop new methods to infer pathway structure by both of interaction data...
September 21, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28950876/a-two-step-framework-for-inferring-direct-protein-protein-interaction-network-from-ap-ms-data
#18
Bo Tian, Can Zhao, Feiyang Gu, Zengyou He
BACKGROUND: Affinity purification-mass spectrometry (AP-MS) has been widely used for generating bait-prey data sets so as to identify underlying protein-protein interactions and protein complexes. However, the AP-MS data sets in terms of bait-prey pairs are highly noisy, where candidate pairs contain many false positives. Recently, numerous computational methods have been developed to identify genuine interactions from AP-MS data sets. However, most of these methods aim at removing false positives that contain contaminants, ignoring the distinction between direct interactions and indirect interactions...
September 21, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28950873/modeling-and-analysis-of-the-delta-notch-dependent-boundary-formation-in-the-drosophila-large-intestine
#19
Fei Liu, Deshun Sun, Ryutaro Murakami, Hiroshi Matsuno
BACKGROUND: The boundary formation in the Drosophila large intestine is widely studied as an important biological problem. It has been shown that the Delta-Notch signaling pathway plays an essential role in the formation of boundary cells. RESULTS: In this paper, we propose a mathematical model for the Delta-Notch dependent boundary formation in the Drosophila large intestine in order to better interpret related experimental findings of this biological phenomenon...
September 21, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/28950872/forecasting-influenza-a-pandemic-outbreak-using-protein-dynamical-network-biomarkers
#20
Jie Gao, Kang Wang, Tao Ding, Shanshan Zhu
BACKGROUND: Influenza A virus is prone to mutation and susceptible to human beings and spread in the crowds when affected by the external environment or other factors. It is very necessary to forecast influenza A pandemic outbreak. METHODS: This paper studies the different states of influenza A in the method of dynamical network biomarkers. Through establishing protein dynamical network biomarkers of influenza A virus protein, a composite index is ultimately obtained to forecast influenza A pandemic outbreak...
September 21, 2017: BMC Systems Biology
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