1,954 results match your criteria Bmc Systems Biology[Journal]


Predicting disease-related phenotypes using an integrated phenotype similarity measurement based on HPO.

BMC Syst Biol 2019 Apr 5;13(Suppl 2):34. Epub 2019 Apr 5.

School of Computer Science, Northwestern Polytechnical University, Xi'an, China.

Background: Improving efficiency of disease diagnosis based on phenotype ontology is a critical yet challenging research area. Recently, Human Phenotype Ontology (HPO)-based semantic similarity has been affectively and widely used to identify causative genes and diseases. However, current phenotype similarity measurements just consider the annotations and hierarchy structure of HPO, neglecting the definition description of phenotype terms. Read More

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http://dx.doi.org/10.1186/s12918-019-0697-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449884PMC
April 2019
1 Read

Fusing gene expressions and transitive protein-protein interactions for inference of gene regulatory networks.

BMC Syst Biol 2019 Apr 5;13(Suppl 2):37. Epub 2019 Apr 5.

School of Computer Engineering, Nanyang Technological University, Singapore, Singapore.

Background: Systematic fusion of multiple data sources for Gene Regulatory Networks (GRN) inference remains a key challenge in systems biology. We incorporate information from protein-protein interaction networks (PPIN) into the process of GRN inference from gene expression (GE) data. However, existing PPIN remain sparse and transitive protein interactions can help predict missing protein interactions. Read More

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http://dx.doi.org/10.1186/s12918-019-0695-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449891PMC

A fast and efficient count-based matrix factorization method for detecting cell types from single-cell RNAseq data.

BMC Syst Biol 2019 Apr 5;13(Suppl 2):28. Epub 2019 Apr 5.

School of Computer Science, Northwestern Polytechnical University, Xi'an, Shaanxi, 710129, People's Republic of China.

Background: Single-cell RNA sequencing (scRNAseq) data always involves various unwanted variables, which would be able to mask the true signal to identify cell-types. More efficient way of dealing with this issue is to extract low dimension information from high dimensional gene expression data to represent cell-type structure. In the past two years, several powerful matrix factorization tools were developed for scRNAseq data, such as NMF, ZIFA, pCMF and ZINB-WaVE. Read More

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http://dx.doi.org/10.1186/s12918-019-0699-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449882PMC
April 2019
1 Read

GNE: a deep learning framework for gene network inference by aggregating biological information.

BMC Syst Biol 2019 Apr 5;13(Suppl 2):38. Epub 2019 Apr 5.

Golisano College of Computing and Information Sciences, Rochester Institute of Technology, 20 Lomb Memorial Drive, Rochester, New York, 14623, USA.

Background: The topological landscape of gene interaction networks provides a rich source of information for inferring functional patterns of genes or proteins. However, it is still a challenging task to aggregate heterogeneous biological information such as gene expression and gene interactions to achieve more accurate inference for prediction and discovery of new gene interactions. In particular, how to generate a unified vector representation to integrate diverse input data is a key challenge addressed here. Read More

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https://bmcsystbiol.biomedcentral.com/articles/10.1186/s1291
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http://dx.doi.org/10.1186/s12918-019-0694-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449883PMC
April 2019
1 Read

FCMDAP: using miRNA family and cluster information to improve the prediction accuracy of disease related miRNAs.

BMC Syst Biol 2019 Apr 5;13(Suppl 2):26. Epub 2019 Apr 5.

Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.

Background: Biological experiments have confirmed the association between miRNAs and various diseases. However, such experiments are costly and time consuming. Computational methods help select potential disease-related miRNAs to improve the efficiency of biological experiments. Read More

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http://dx.doi.org/10.1186/s12918-019-0696-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449885PMC

Anti-TNF- αtreatment-related pathways and biomarkers revealed by transcriptome analysis in Chinese psoriasis patients.

BMC Syst Biol 2019 Apr 5;13(Suppl 2):29. Epub 2019 Apr 5.

Department of Dermatology, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.

Background: Anti-tumor necrosis factor alpha (TNF- α) therapy has made a significant impact on treating psoriasis. Despite these agents being designed to block TNF- α activity, their mechanism of action in the remission of psoriasis is still not fully understood at the molecular level.

Results: To better understand the molecular mechanisms of Anti-TNF- α therapy, we analysed the global gene expression profile (using mRNA microarray) in peripheral blood mononuclear cells (PBMCs) that were collected from 6 psoriasis patients before and 12 weeks after the treatment of etanercept. Read More

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http://dx.doi.org/10.1186/s12918-019-0698-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449888PMC
April 2019
1 Read

Ultrafast clustering of single-cell flow cytometry data using FlowGrid.

BMC Syst Biol 2019 Apr 5;13(Suppl 2):35. Epub 2019 Apr 5.

Victor Chang Cardiac Research Institute, Sydney, Australia.

Background: Flow cytometry is a popular technology for quantitative single-cell profiling of cell surface markers. It enables expression measurement of tens of cell surface protein markers in millions of single cells. It is a powerful tool for discovering cell sub-populations and quantifying cell population heterogeneity. Read More

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http://dx.doi.org/10.1186/s12918-019-0690-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449887PMC
April 2019
1 Read
2.435 Impact Factor

Boolean network modeling of β-cell apoptosis and insulin resistance in type 2 diabetes mellitus.

BMC Syst Biol 2019 Apr 5;13(Suppl 2):36. Epub 2019 Apr 5.

School of Information Science and Technology, ShanghaiTech University, Shanghai, China.

Background: Major alteration in lifestyle of human population has promoted Type 2 diabetes mellitus (T2DM) to the level of an epidemic. This metabolic disorder is characterized by insulin resistance and pancreatic β-cell dysfunction and apoptosis, triggered by endoplasmic reticulum (ER) stress, oxidative stress and cytokines. Computational modeling is necessary to consolidate information from various sources in order to obtain a comprehensive understanding of the pathogenesis of T2DM and to investigate possible interventions by performing in silico simulations. Read More

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http://dx.doi.org/10.1186/s12918-019-0692-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449890PMC

Network-based characterization of drug-protein interaction signatures with a space-efficient approach.

BMC Syst Biol 2019 Apr 5;13(Suppl 2):39. Epub 2019 Apr 5.

Department of Bioscience and Bioinformatics, Faculty of Computer Science and Systems Engineering, Kyushu Institute of Technology, 680-4 Kawazu, Lizuka, Fukuoka, 820-8502, Japan.

Background: Characterization of drug-protein interaction networks with biological features has recently become challenging in recent pharmaceutical science toward a better understanding of polypharmacology.

Results: We present a novel method for systematic analyses of the underlying features characteristic of drug-protein interaction networks, which we call "drug-protein interaction signatures" from the integration of large-scale heterogeneous data of drugs and proteins. We develop a new efficient algorithm for extracting informative drug-protein interaction signatures from the integration of large-scale heterogeneous data of drugs and proteins, which is made possible by space-efficient representations for fingerprints of drug-protein pairs and sparsity-induced classifiers. Read More

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http://dx.doi.org/10.1186/s12918-019-0691-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449886PMC
April 2019
2 Reads

Identification of Hürthle cell cancers: solving a clinical challenge with genomic sequencing and a trio of machine learning algorithms.

BMC Syst Biol 2019 Apr 5;13(Suppl 2):27. Epub 2019 Apr 5.

Department of Research & Development, Veracyte, Inc, 6000 Shoreline Court, Suite 300, South San Francisco, CA, 94080, USA.

Background: Identification of Hürthle cell cancers by non-operative fine-needle aspiration biopsy (FNAB) of thyroid nodules is challenging. Resultingly, non-cancerous Hürthle lesions were conventionally distinguished from Hürthle cell cancers by histopathological examination of tissue following surgical resection. Reliance on histopathological evaluation requires patients to undergo surgery to obtain a diagnosis despite most being non-cancerous. Read More

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https://bmcsystbiol.biomedcentral.com/articles/10.1186/s1291
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http://dx.doi.org/10.1186/s12918-019-0693-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6450053PMC
April 2019
2 Reads

PMAMCA: prediction of microRNA-disease association utilizing a matrix completion approach.

BMC Syst Biol 2019 Mar 20;13(1):33. Epub 2019 Mar 20.

Department of Computer Science, Yonsei University, 134 Sinchon-dong, Seodaemun-gu, Seoul, South Korea.

Background: Numerous experimental results have indicated that microRNAs (miRNAs) play a vital role in biological processes, as well as outbreaks of diseases at the molecular level. Despite their important role in biological processes, knowledge regarding specific functions of miRNAs in the development of human diseases is very limited. While attempting to solve this problem, many computational approaches have been proposed and attracted significant attention. Read More

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http://dx.doi.org/10.1186/s12918-019-0700-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6425656PMC

How to schedule VEGF and PD-1 inhibitors in combination cancer therapy?

BMC Syst Biol 2019 Mar 13;13(1):30. Epub 2019 Mar 13.

Mathematical Bioscience Institute & Department of Mathematics, Ohio State University, Columbus, OH, USA.

Background: One of the questions in the design of cancer clinical trials with combination of two drugs is in which order to administer the drugs. This is an important question, especially in the case where one agent may interfere with the effectiveness of the other agent.

Results: In the present paper we develop a mathematical model to address this scheduling question in a specific case where one of the drugs is anti-VEGF, which is known to affect the perfusion of other drugs. Read More

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http://dx.doi.org/10.1186/s12918-019-0706-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6427900PMC

Adaptive information processing of network modules to dynamic and spatial stimuli.

BMC Syst Biol 2019 Mar 14;13(1):32. Epub 2019 Mar 14.

Department of Chemical Engineering, Centre for Process Systems Engineering, Imperial College London, South Kensington, London, SW7 2AZ, UK.

Background: Adaptation and homeostasis are basic features of information processing in cells and seen in a broad range of contexts. Much of the current understanding of adaptation in network modules/motifs is based on their response to simple stimuli. Recently, there have also been studies of adaptation in dynamic stimuli. Read More

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http://dx.doi.org/10.1186/s12918-019-0703-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6417070PMC

Correction to: Pathway crosstalk perturbation network modeling for identification of connectivity changes induced by diabetic neuropathy and pioglitazone.

BMC Syst Biol 2019 Mar 13;13(1):31. Epub 2019 Mar 13.

Department of Biomedical Sciences, University of North Dakota School of Medicine and Health Sciences, Grand Forks, North Dakota, 58202, USA.

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http://dx.doi.org/10.1186/s12918-019-0707-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6416955PMC
March 2019
1 Read
2.435 Impact Factor

Effects of unpaired 1 gene overexpression on the lifespan of Drosophila melanogaster.

BMC Syst Biol 2019 Mar 5;13(Suppl 1):16. Epub 2019 Mar 5.

Institute of Biology, Komi Scientific Center, Ural Division, Russian Academy of Sciences, Syktyvkar, 167982, Russia.

Background: The JAK/STAT signaling pathway is involved in many aging-related cellular functions. However, effects of overexpression of genes controlling JAK/STAT signal transduction on longevity of model organisms have not been studied. Here we evaluate the effect of overexpression of the unpaired 1 (upd1) gene, which encodes an activating ligand for JAK/STAT pathway, on the lifespan of Drosophila melanogaster. Read More

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https://bmcsystbiol.biomedcentral.com/articles/10.1186/s1291
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http://dx.doi.org/10.1186/s12918-019-0687-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6399815PMC
March 2019
3 Reads

Towards embedding Caco-2 model of gut interface in a microfluidic device to enable multi-organ models for systems biology.

BMC Syst Biol 2019 Mar 5;13(Suppl 1):19. Epub 2019 Mar 5.

SRC BioClinicum, Moscow, Russia.

Background: A cancer cell line originating from human epithelial colorectal adenocarcinoma (Caco-2 cells) serves as a high capacity model for a preclinical screening of drugs. Recent need for incorporating barrier tissue into multi-organ chips calls for inclusion of Caco-2 cells into microperfused environment.

Results: This article describes a series of systems biology insights obtained from comparing Caco-2 models cells grown as conventional 2D layer and in a microfluidic chip. Read More

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http://dx.doi.org/10.1186/s12918-019-0686-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6399809PMC
March 2019
7 Reads

Urine proteome changes associated with autonomic regulation of heart rate in cosmonauts.

BMC Syst Biol 2019 Mar 5;13(Suppl 1):17. Epub 2019 Mar 5.

Institute for Biomedical Problems - Russian Federation State Scientific Research Center Russian Academy of Sciences, Moscow, Russia.

Background: The strategy of adaptation of the human body in microgravity is largely associated with the plasticity of cardiovascular system regulatory mechanisms. During long-term space flights the changes in the stroke volume of the heart are observed, the heart rate decreases, the phase structure of cardiac cycle is readjusted The purpose of this work was to clarify urine proteome changes associated with the initial condition of the heart rate autonomic regulation mechanisms in cosmonauts who have participated in long space missions. Urine proteome of each cosmonaut was analyzed before and after space flight, depending on the initial parameters characterizing the regulatory mechanisms of the cardiovascular system. Read More

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https://bmcsystbiol.biomedcentral.com/articles/10.1186/s1291
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http://dx.doi.org/10.1186/s12918-019-0688-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6399814PMC
March 2019
5 Reads

Systems biology research at BGRS-2018.

BMC Syst Biol 2019 Mar 5;13(Suppl 1):21. Epub 2019 Mar 5.

School of Systems Biology, George Mason University, Fairfax, VA, USA.

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http://dx.doi.org/10.1186/s12918-019-0685-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6399810PMC

LSM-W: laser scanning microscopy worker for wheat leaf surface morphology.

BMC Syst Biol 2019 Mar 5;13(Suppl 1):22. Epub 2019 Mar 5.

Institute of Cytology and Genetics SB RAS, Prospekt Lavrentyeva 10, Novosibirsk, 630090, Russia.

Background: Microscopic images are widely used in plant biology as an essential source of information on morphometric characteristics of the cells and the topological characteristics of cellular tissue pattern due to modern computer vision algorithms. High-resolution 3D confocal images allow extracting quantitative characteristics describing the cell structure of leaf epidermis. For some issues in the study of cereal leaves development, it is required to apply the staining techniques with fluorescent dyes and to scan rather large fragments consisting of several frames. Read More

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http://dx.doi.org/10.1186/s12918-019-0689-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6399813PMC

Mathematical modeling of movement on fitness landscapes.

BMC Syst Biol 2019 Feb 28;13(1):25. Epub 2019 Feb 28.

Department of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, 400 076, India.

Background: Movement of populations on fitness landscapes has been a problem of interest for a long time. While the subject has been extensively developed theoretically, reconciliation of the theoretical work with recent experimental data has not yet happened. In this work, we develop a computational framework and study evolution of the simplest transcription network between a single regulator, R and a single target protein, T. Read More

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http://dx.doi.org/10.1186/s12918-019-0704-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6394095PMC
February 2019

Computational modelling of energy balance in individuals with Metabolic Syndrome.

BMC Syst Biol 2019 Feb 26;13(1):24. Epub 2019 Feb 26.

Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.

Background: A positive energy balance is considered to be the primary cause of the development of obesity-related diseases. Treatment often consists of a combination of reducing energy intake and increasing energy expenditure. Here we use an existing computational modelling framework describing the long-term development of Metabolic Syndrome (MetS) in APOE3L. Read More

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http://dx.doi.org/10.1186/s12918-019-0705-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6390597PMC
February 2019
1 Read
2.435 Impact Factor

A mathematical model of iron import and trafficking in wild-type and Mrs3/4ΔΔ yeast cells.

BMC Syst Biol 2019 Feb 21;13(1):23. Epub 2019 Feb 21.

Texas A&M University, Department of Chemistry, College Station, TX, 77843-3255, USA.

Background: Iron plays crucial roles in the metabolism of eukaryotic cells. Much iron is trafficked into mitochondria where it is used for iron-sulfur cluster assembly and heme biosynthesis. A yeast strain in which Mrs3/4, the high-affinity iron importers on the mitochondrial inner membrane, are deleted exhibits a slow-growth phenotype when grown under iron-deficient conditions. Read More

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http://dx.doi.org/10.1186/s12918-019-0702-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6385441PMC
February 2019

Correction to: miRNAs and target genes in the blood as biomarkers for the early diagnosis of Parkinson's disease.

BMC Syst Biol 2019 Feb 12;13(1):20. Epub 2019 Feb 12.

Department of Physiology, College of Life Science, Hebei Normal University, Shijiazhuang, China.

AbstractIt was highlighted that the original article [1] contained some typesetting mistakes in the first paragraph of the Background section. Read More

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http://dx.doi.org/10.1186/s12918-019-0701-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6372997PMC
February 2019

In-silico comparison of two induction regimens (7 + 3 vs 7 + 3 plus additional bone marrow evaluation) in acute myeloid leukemia treatment.

BMC Syst Biol 2019 Jan 31;13(1):18. Epub 2019 Jan 31.

Institute of Biostatistics and Clinical Research, Westfälische Wilhelms-Universität Münster, Münster, Germany.

Background: Clinical integration of systems biology approaches is gaining in importance in the course of digital revolution in modern medicine. We present our results of the analysis of an extended mathematical model describing abnormal human hematopoiesis. The model is able to describe the course of an acute myeloid leukemia including its treatment. Read More

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http://dx.doi.org/10.1186/s12918-019-0684-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6357450PMC
January 2019
1 Read

How to prevent viremia rebound? Evidence from a PRRSv data-supported model of immune response.

BMC Syst Biol 2019 Jan 29;13(1):15. Epub 2019 Jan 29.

Division of Genetics and Genomics, The Roslin Institute, Easter Bush, Midlothian, UK.

Background: Understanding what determines the between-host variability in infection dynamics is a key issue to better control the infection spread. In particular, pathogen clearance is desirable over rebounds for the health of the infected individual and its contact group. In this context, the Porcine Respiratory and Reproductive Syndrome virus (PRRSv) is of particular interest. Read More

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https://bmcsystbiol.biomedcentral.com/articles/10.1186/s1291
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http://dx.doi.org/10.1186/s12918-018-0666-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6352383PMC
January 2019
4 Reads

Correction to: circular RNA expression profiles during the differentiation of mouse neural stem cells.

BMC Syst Biol 2019 Jan 24;13(1):14. Epub 2019 Jan 24.

The First Affiliated Hospital with Nanjing Medical University, Nanjing, 210019, Jiangsu, China.

It was highlighted that the original article [1] contained a mistake in the grant number in the Funding section of the Declarations, and in the legend of Fig. 6. This Correction article shows the incorrect and correct version of the Funding and the legend of Fig. Read More

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http://dx.doi.org/10.1186/s12918-019-0682-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6345063PMC
January 2019
2.435 Impact Factor

Correction to: MISC: missing imputation for single-cell RNA sequencing data.

BMC Syst Biol 2019 Jan 22;13(1):13. Epub 2019 Jan 22.

Joint Bioinformatics Program, University of Arkansas Little Rock George Washington Donaghey College of Engineering & IT and University of Arkansas for Medical Sciences, Little Rock, AR, 72204, USA.

It was highlighted that the original article [1] contained a typesetting error in the last name of Allon Canaan. This was incorrectly captured as Allon Canaann in the original article which has since been updated. Read More

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http://dx.doi.org/10.1186/s12918-019-0681-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6343234PMC
January 2019
1 Read

A mathematical model to estimate cholesterylester transfer protein (CETP) triglycerides flux in human plasma.

BMC Syst Biol 2019 Jan 22;13(1):12. Epub 2019 Jan 22.

Institute of Clinical Chemistry and Laboratory Medicine, Medical Centre - University of Freiburg, Freiburg im Breisgau, Germany.

Background: Cholesterylester transfer protein (CETP) modulates the composition of various lipoproteins associated with cardiovascular disease. Despite its central role in lipoprotein metabolism, its mode of action is still not fully understood. Here we present a simple way to estimate CETP-mediated lipid fluxes between different lipoprotein fractions. Read More

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http://dx.doi.org/10.1186/s12918-019-0679-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6341636PMC
January 2019
1 Read

miRNAs and target genes in the blood as biomarkers for the early diagnosis of Parkinson's disease.

BMC Syst Biol 2019 Jan 21;13(1):10. Epub 2019 Jan 21.

Department of Physiology, College of Life Sciences, Hebei Normal University, Shijiazhuang, China.

Background: Parkinson's disease (PD) is the second most common neurodegenerative disease, and it is a multifactorial disease with no definite diagnostic index. The aim of this study is to construct a molecular network to find molecules that play important roles in the progression of PD with the goal of using them diagnostically and for early intervention.

Results: We downloaded two gene expression profiles (GSE54536 and GSE100054) from the Expression Omnibus (GEO) database to analyze possible markers. Read More

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http://dx.doi.org/10.1186/s12918-019-0680-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6341689PMC
January 2019
4 Reads

Use of genome-scale models to get new insights into the marine actinomycete genus Salinispora.

BMC Syst Biol 2019 Jan 21;13(1):11. Epub 2019 Jan 21.

Centre for Biotechnology and Bioengineering (CeBiB), Department of Chemical Engineering, Biotechnology and Materials, University of Chile, Beauchef 851, Santiago, Chile.

Background: There is little published regarding metabolism of Salinispora species. In continuation with efforts performed towards this goal, this study is focused on new insights into the metabolism of the three-identified species of Salinispora using constraints-based modeling. At present, only one manually curated genome-scale metabolic model (GSM) for Salinispora tropica strain CNB-440 has been built despite the role of Salinispora strains in drug discovery. Read More

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http://dx.doi.org/10.1186/s12918-019-0683-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6341766PMC
January 2019

Model-based virtual patient analysis of human liver regeneration predicts critical perioperative factors controlling the dynamic mode of response to resection.

BMC Syst Biol 2019 Jan 16;13(1). Epub 2019 Jan 16.

Daniel Baugh Institute for Functional Genomics/Computational Biology, Department of Pathology, Anatomy, and Cell Biology, Thomas Jefferson University, Philadelphia, PA, USA.

Background: Liver has the unique ability to regenerate following injury, with a wide range of variability of the regenerative response across individuals. Existing computational models of the liver regeneration are largely tuned based on rodent data and hence it is not clear how well these models capture the dynamics of human liver regeneration. Recent availability of human liver volumetry time series data has enabled new opportunities to tune the computational models for human-relevant time scales, and to predict factors that can significantly alter the dynamics of liver regeneration following a resection. Read More

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https://bmcsystbiol.biomedcentral.com/articles/10.1186/s1291
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http://dx.doi.org/10.1186/s12918-019-0678-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6335689PMC
January 2019
12 Reads

An agent-based model of the Notch signaling pathway elucidates three levels of complexity in the determination of developmental patterning.

BMC Syst Biol 2019 Jan 14;13(1). Epub 2019 Jan 14.

Computer Science Department, Lafayette College, Easton, PA, 18042, USA.

Background: The Notch signaling pathway is involved in cell fate decision and developmental patterning in diverse organisms. A receptor molecule, Notch (N), and a ligand molecule (in this case Delta or Dl) are the central molecules in this pathway. In early Drosophila embryos, these molecules determine neural vs. Read More

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http://dx.doi.org/10.1186/s12918-018-0672-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6332573PMC
January 2019
1 Read

Multi-omics integration reveals molecular networks and regulators of psoriasis.

BMC Syst Biol 2019 Jan 14;13(1). Epub 2019 Jan 14.

Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Dr. East, Los Angeles, CA, 90095, USA.

Background: Psoriasis is a complex multi-factorial disease, involving both genetic susceptibilities and environmental triggers. Genome-wide association studies (GWAS) and epigenome-wide association studies (EWAS) have been carried out to identify genetic and epigenetic variants that are associated with psoriasis. However, these loci cannot fully explain the disease pathogenesis. Read More

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https://bmcsystbiol.biomedcentral.com/articles/10.1186/s1291
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http://dx.doi.org/10.1186/s12918-018-0671-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6332659PMC
January 2019
6 Reads

Plasmodium vivax readiness to transmit: implication for malaria eradication.

BMC Syst Biol 2019 Jan 11;13(1). Epub 2019 Jan 11.

Department of Global Health (GH) & Center for Drug Discovery and Innovation (CDDI), College of Public Health, University of South Florida, Tampa, FL, 33612, USA.

Background: The lack of a continuous long-term in vitro culture system for Plasmodium vivax severely limits our knowledge of pathophysiology of the most widespread malaria parasite. To gain direct understanding of P. vivax human infections, we used Next Generation Sequencing data mining to unravel parasite in vivo expression profiles for P. Read More

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http://dx.doi.org/10.1186/s12918-018-0669-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6330404PMC
January 2019
1 Read

Constructing network topologies for multiple signal-encoding functions.

BMC Syst Biol 2019 Jan 11;13(1). Epub 2019 Jan 11.

The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics, School of Physics, Peking University, Beijing, 100871, China.

Background: Cells use signaling protein networks to sense their environment and mediate specific responses. Information about environmental stress is usually encoded in the dynamics of the signaling molecules, and qualitatively distinct dynamics of the same signaling molecule can lead to dramatically different cell fates. Exploring the design principles of networks with multiple signal-encoding functions is important for understanding how distinct dynamic patterns are shaped and integrated by real cellular networks, and for building cells with targeted sensing-response functions via synthetic biology. Read More

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https://bmcsystbiol.biomedcentral.com/articles/10.1186/s1291
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http://dx.doi.org/10.1186/s12918-018-0676-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6330498PMC
January 2019
6 Reads

SLIMEr: probing flexibility of lipid metabolism in yeast with an improved constraint-based modeling framework.

BMC Syst Biol 2019 Jan 11;13(1). Epub 2019 Jan 11.

Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.

Background: A recurrent problem in genome-scale metabolic models (GEMs) is to correctly represent lipids as biomass requirements, due to the numerous of possible combinations of individual lipid species and the corresponding lack of fully detailed data. In this study we present SLIMEr, a formalism for correctly representing lipid requirements in GEMs using commonly available experimental data.

Results: SLIMEr enhances a GEM with mathematical constructs where we Split Lipids Into Measurable Entities (SLIME reactions), in addition to constraints on both the lipid classes and the acyl chain distribution. Read More

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http://dx.doi.org/10.1186/s12918-018-0673-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6330394PMC
January 2019
2 Reads

Modelling overflow metabolism in Escherichia coli with flux balance analysis incorporating differential proteomic efficiencies of energy pathways.

BMC Syst Biol 2019 Jan 10;13(1). Epub 2019 Jan 10.

Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ, UK.

Background: The formation of acetate by fast-growing Escherichia coli (E. coli) is a commonly observed phenomenon, often referred to as overflow metabolism. Among various studies that have been carried over decades, a recent work (Basan, M. Read More

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http://dx.doi.org/10.1186/s12918-018-0677-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6329140PMC
January 2019
3 Reads

DynamicME: dynamic simulation and refinement of integrated models of metabolism and protein expression.

BMC Syst Biol 2019 Jan 9;13(1). Epub 2019 Jan 9.

Department of Bioengineering, University of California at San Diego, 9500 Gilman Drive, La Jolla, 92093, CA, USA.

Background: Genome-scale models of metabolism and macromolecular expression (ME models) enable systems-level computation of proteome allocation coupled to metabolic phenotype.

Results: We develop DynamicME, an algorithm enabling time-course simulation of cell metabolism and protein expression. DynamicME correctly predicted the substrate utilization hierarchy on a mixed carbon substrate medium. Read More

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http://dx.doi.org/10.1186/s12918-018-0675-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6327497PMC
January 2019
3 Reads

Pathway crosstalk perturbation network modeling for identification of connectivity changes induced by diabetic neuropathy and pioglitazone.

BMC Syst Biol 2019 Jan 7;13(1). Epub 2019 Jan 7.

Department of Biomedical Sciences, University of North Dakota School of Medicine and Health Sciences, Grand Forks, North Dakota, 58202, USA.

Background: Aggregation of high-throughput biological data using pathway-based approaches is useful to associate molecular results to functional features related to the studied phenomenon. Biological pathways communicate with one another through the crosstalk phenomenon, forming large networks of interacting processes.

Results: In this work, we present the pathway crosstalk perturbation network (PXPN) model, a novel model used to analyze and integrate pathway perturbation data based on graph theory. Read More

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http://dx.doi.org/10.1186/s12918-018-0674-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6322225PMC
January 2019
3 Reads
2.435 Impact Factor

Integrating node embeddings and biological annotations for genes to predict disease-gene associations.

BMC Syst Biol 2018 12 31;12(Suppl 9):138. Epub 2018 Dec 31.

Data Analytics Department, Institute for Infocomm Research, Singapore, Singapore.

Background: Predicting disease causative genes (or simply, disease genes) has played critical roles in understanding the genetic basis of human diseases and further providing disease treatment guidelines. While various computational methods have been proposed for disease gene prediction, with the recent increasing availability of biological information for genes, it is highly motivated to leverage these valuable data sources and extract useful information for accurately predicting disease genes.

Results: We present an integrative framework called N2VKO to predict disease genes. Read More

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http://dx.doi.org/10.1186/s12918-018-0662-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6311944PMC
December 2018
1 Read

Analysis of significant protein abundance from multiple reaction-monitoring data.

BMC Syst Biol 2018 12 31;12(Suppl 9):123. Epub 2018 Dec 31.

Department of Statistics, Seoul National University, Seoul, South Korea.

Background: Discovering reliable protein biomarkers is one of the most important issues in biomedical research. The ELISA is a traditional technique for accurate quantitation of well-known proteins. Recently, the multiple reaction-monitoring (MRM) mass spectrometry has been proposed for quantifying newly discovered protein and has become a popular alternative to ELISA. Read More

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http://dx.doi.org/10.1186/s12918-018-0656-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6311902PMC
December 2018
5 Reads

A unified solution for different scenarios of predicting drug-target interactions via triple matrix factorization.

BMC Syst Biol 2018 12 31;12(Suppl 9):136. Epub 2018 Dec 31.

Department of Computer Science, The University of Hong Kong, Hong Kong, China.

Background: During the identification of potential candidates, computational prediction of drug-target interactions (DTIs) is important to subsequent expensive validation in wet-lab. DTI screening considers four scenarios, depending on whether the drug is an existing or a new drug and whether the target is an existing or a new target. However, existing approaches have the following limitations. Read More

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http://dx.doi.org/10.1186/s12918-018-0663-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6311903PMC
December 2018
1 Read

Optimizing gene set annotations combining GO structure and gene expression data.

BMC Syst Biol 2018 12 31;12(Suppl 9):133. Epub 2018 Dec 31.

School of Computer Science and Technology, Harbin Institute of Technology, West Da-Zhi Street, Harbin, China.

Background: With the rapid accumulation of genomic data, it has become a challenge issue to annotate and interpret these data. As a representative, Gene set enrichment analysis has been widely used to interpret large molecular datasets generated by biological experiments. The result of gene set enrichment analysis heavily relies on the quality and integrity of gene set annotations. Read More

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http://dx.doi.org/10.1186/s12918-018-0659-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6311910PMC
December 2018
1 Read
2.435 Impact Factor

Hot spot prediction in protein-protein interactions by an ensemble system.

BMC Syst Biol 2018 12 31;12(Suppl 9):132. Epub 2018 Dec 31.

Advanced Analytics Institute and Centre for Health Technologies, University of Technology, Sydney, Sydney, Broadway, NSW, 2007, Australia.

Background: Hot spot residues are functional sites in protein interaction interfaces. The identification of hot spot residues is time-consuming and laborious using experimental methods. In order to address the issue, many computational methods have been developed to predict hot spot residues. Read More

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http://dx.doi.org/10.1186/s12918-018-0665-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6311905PMC
December 2018
1 Read

FMSM: a novel computational model for predicting potential miRNA biomarkers for various human diseases.

BMC Syst Biol 2018 12 31;12(Suppl 9):121. Epub 2018 Dec 31.

Department of Computing, Hong Kong Polytechnic University, Hong Kong, 999077, China.

Background: MicroRNA (miRNA) plays a key role in regulation mechanism of human biological processes, including the development of disease and disorder. It is necessary to identify potential miRNA biomarkers for various human diseases. Computational prediction model is expected to accelerate the process of identification. Read More

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http://dx.doi.org/10.1186/s12918-018-0664-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6311922PMC
December 2018
1 Read

Laplacian normalization and bi-random walks on heterogeneous networks for predicting lncRNA-disease associations.

BMC Syst Biol 2018 12 31;12(Suppl 9):122. Epub 2018 Dec 31.

School of Mathematics and Computational Science, Xiangtan University, Hunan, 411105, China.

Background: Evidences have increasingly indicated that lncRNAs (long non-coding RNAs) are deeply involved in important biological regulation processes leading to various human complex diseases. Experimental investigations of these disease associated lncRNAs are slow with high costs. Computational methods to infer potential associations between lncRNAs and diseases have become an effective prior-pinpointing approach to the experimental verification. Read More

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http://dx.doi.org/10.1186/s12918-018-0660-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6311918PMC
December 2018
1 Read

Multi-CSAR: a multiple reference-based contig scaffolder using algebraic rearrangements.

BMC Syst Biol 2018 12 31;12(Suppl 9):139. Epub 2018 Dec 31.

Department of Computer Science, National Tsing Hua University, Hsinchu, 30013, Taiwan.

Background: One of the important steps in the process of assembling a genome sequence from short reads is scaffolding, in which the contigs in a draft genome are ordered and oriented into scaffolds. Currently, several scaffolding tools based on a single reference genome have been developed. However, a single reference genome may not be sufficient alone for a scaffolder to generate correct scaffolds of a target draft genome, especially when the evolutionary relationship between the target and reference genomes is distant or some rearrangements occur between them. Read More

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http://dx.doi.org/10.1186/s12918-018-0654-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6311912PMC
December 2018
1 Read

rPCMP: robust p-value combination by multiple partitions with applications to ATAC-seq data.

BMC Syst Biol 2018 12 31;12(Suppl 9):141. Epub 2018 Dec 31.

School of Mathematics and Statistics, Xi'an Jiaotong University, Xianning West 28, Xi'an, China.

Background: Evaluating the significance for a group of genes or proteins in a pathway or biological process for a disease could help researchers understand the mechanism of the disease. For example, identifying related pathways or gene functions for chromatin states of tumor-specific T cells will help determine whether T cells could reprogram or not, and further help design the cancer treatment strategy. Some existing p-value combination methods can be used in this scenario. Read More

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http://dx.doi.org/10.1186/s12918-018-0661-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6311921PMC
December 2018
1 Read

Network-based logistic regression integration method for biomarker identification.

BMC Syst Biol 2018 12 31;12(Suppl 9):135. Epub 2018 Dec 31.

Center for Computational Systems Biology, Shanghai Key Laboratory for Contemporary Applied Mathematics, School of Mathematical Sciences, Fudan University, No.220 Handan Road, Shanghai, 200433, China.

Background: Many mathematical and statistical models and algorithms have been proposed to do biomarker identification in recent years. However, the biomarkers inferred from different datasets suffer a lack of reproducibilities due to the heterogeneity of the data generated from different platforms or laboratories. This motivates us to develop robust biomarker identification methods by integrating multiple datasets. Read More

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http://dx.doi.org/10.1186/s12918-018-0657-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6311907PMC
December 2018
4 Reads

Computational drug repositioning using meta-path-based semantic network analysis.

BMC Syst Biol 2018 12 31;12(Suppl 9):134. Epub 2018 Dec 31.

School of Electrical and Information Engineering, Beijing University of Civil Engineering and Architecture, Beijing, 100044, People's Republic of China.

Background: Drug repositioning is a promising and efficient way to discover new indications for existing drugs, which holds the great potential for precision medicine in the post-genomic era. Many network-based approaches have been proposed for drug repositioning based on similarity networks, which integrate multiple sources of drugs and diseases. However, these methods may simply view nodes as the same-typed and neglect the semantic meanings of different meta-paths in the heterogeneous network. Read More

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http://dx.doi.org/10.1186/s12918-018-0658-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6311940PMC
December 2018
1 Read