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Networks analysis

Section edited by Jean-Philippe Vert

This section incorporates all aspects of network analysis including but not limited to: methods for predicting, analyzing and visualizing networks, and applications to systems biology.

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  1. An organism’s protein interactome, or complete network of protein-protein interactions, defines the protein complexes that drive cellular processes. Techniques for studying protein complexes have traditionally...

    Authors: R. Greg Stacey, Michael A. Skinnider, Nichollas E. Scott and Leonard J. Foster

    Citation: BMC Bioinformatics 2017 18:457

    Content type: Research Article

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  2. Computational fusion approaches to drug-target interaction (DTI) prediction, capable of utilizing multiple sources of background knowledge, were reported to achieve superior predictive performance in multiple ...

    Authors: Bence Bolgár and Péter Antal

    Citation: BMC Bioinformatics 2017 18:440

    Content type: Research Article

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  3. Colorectal cancer (CRC) is one of the most common malignancies worldwide with poor prognosis. Studies have showed that abnormal microRNA (miRNA) expression can affect CRC pathogenesis and development through t...

    Authors: Hao Wang, Jiamao Luo, Chun Liu, Huilin Niu, Jing Wang, Qi Liu, Zhongming Zhao, Hua Xu, Yanqing Ding, Jingchun Sun and Qingling Zhang

    Citation: BMC Bioinformatics 2017 18:388

    Content type: Research Article

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  4. As more and more biological reaction data become available, the full exploration of the enzymatic potential for the synthesis of valuable products opens up exciting new opportunities but is becoming increasing...

    Authors: Lisa Katharina Blaß, Christian Weyler and Elmar Heinzle

    Citation: BMC Bioinformatics 2017 18:366

    Content type: Research Article

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  5. sgnesR (Stochastic Gene Network Expression Simulator in R) is an R package that provides an interface to simulate gene expression data from a given gene network using the stochastic simulation algorithm (SSA)....

    Authors: Shailesh Tripathi, Jason Lloyd-Price, Andre Ribeiro, Olli Yli-Harja, Matthias Dehmer and Frank Emmert-Streib

    Citation: BMC Bioinformatics 2017 18:325

    Content type: Software

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  6. Colorectal carcinoma evolves through a multitude of molecular events including somatic mutations, epigenetic alterations, and aberrant protein expression, influenced by host immune reactions. One way to interr...

    Authors: Reiko Nishihara, Kimberly Glass, Kosuke Mima, Tsuyoshi Hamada, Jonathan A. Nowak, Zhi Rong Qian, Peter Kraft, Edward L. Giovannucci, Charles S. Fuchs, Andrew T. Chan, John Quackenbush, Shuji Ogino and Jukka-Pekka Onnela

    Citation: BMC Bioinformatics 2017 18:304

    Content type: Research Article

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  7. Many biological pathways have been created to represent different types of knowledge, such as genetic interactions, metabolic reactions, and gene-regulating and physical-binding relationships. Biologists are u...

    Authors: Wenjian Xu, Yang Cao, Ziwei Xie, Haochen He, Song He, Hao Hong, Xiaochen Bo and Fei Li

    Citation: BMC Bioinformatics 2017 18:262

    Content type: Software

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  8. Mathematical modeling and in silico analysis are widely acknowledged as complementary tools to biological laboratory methods, to achieve a thorough understanding of emergent behaviors of cellular processes in ...

    Authors: Andrea Tangherloni, Marco S. Nobile, Daniela Besozzi, Giancarlo Mauri and Paolo Cazzaniga

    Citation: BMC Bioinformatics 2017 18:246

    Content type: Research Article

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  9. Modeling of microbial metabolism is a topic of growing importance in biotechnology. Mathematical modeling helps provide a mechanistic understanding for the studied process, separating the main drivers from the...

    Authors: Garrett W. Birkel, Amit Ghosh, Vinay S. Kumar, Daniel Weaver, David Ando, Tyler W. H. Backman, Adam P. Arkin, Jay D. Keasling and Héctor García Martín

    Citation: BMC Bioinformatics 2017 18:205

    Content type: Software

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    The Erratum to this article has been published in BMC Bioinformatics 2017 18:219

  10. Protein-protein interactions (PPIs) can offer compelling evidence for protein function, especially when viewed in the context of proteome-wide interactomes. Bacteria have been popular subjects of interactome s...

    Authors: J. Harry Caufield, Christopher Wimble, Semarjit Shary, Stefan Wuchty and Peter Uetz

    Citation: BMC Bioinformatics 2017 18:171

    Content type: Research article

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  11. With the advancement of high-throughput technologies and enrichment of popular public databases, more and more research focuses of bioinformatics research have been on computational integration of network and ...

    Authors: Hao He, Dongdong Lin, Jigang Zhang, Yu-ping Wang and Hong-wen Deng

    Citation: BMC Bioinformatics 2017 18:149

    Content type: Research article

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  12. Reactome aims to provide bioinformatics tools for visualisation, interpretation and analysis of pathway knowledge to support basic research, genome analysis, modelling, systems biology and education. Pathway a...

    Authors: Antonio Fabregat, Konstantinos Sidiropoulos, Guilherme Viteri, Oscar Forner, Pablo Marin-Garcia, Vicente Arnau, Peter D’Eustachio, Lincoln Stein and Henning Hermjakob

    Citation: BMC Bioinformatics 2017 18:142

    Content type: Software

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  13. Conventional differential gene expression analysis by methods such as student’s t-test, SAM, and Empirical Bayes often searches for statistically significant genes without considering the interactions among them....

    Authors: Yiming Zuo, Yi Cui, Guoqiang Yu, Ruijiang Li and Habtom W. Ressom

    Citation: BMC Bioinformatics 2017 18:99

    Content type: Methodology Article

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  14. The Human Microbiome has been variously associated with the immune-regulatory mechanisms involved in the prevention or development of many non-infectious human diseases such as autoimmunity, allergy and cancer...

    Authors: W. Duncan Wadsworth, Raffaele Argiento, Michele Guindani, Jessica Galloway-Pena, Samuel A. Shelburne and Marina Vannucci

    Citation: BMC Bioinformatics 2017 18:94

    Content type: Methodology Article

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    The Erratum to this article has been published in BMC Bioinformatics 2017 18:185

  15. Knockout strategies, particularly the concept of constrained minimal cut sets (cMCSs), are an important part of the arsenal of tools used in manipulating metabolic networks. Given a specific design, cMCSs can ...

    Authors: Govind Nair, Christian Jungreuthmayer and Jürgen Zanghellini

    Citation: BMC Bioinformatics 2017 18:78

    Content type: Methodology Article

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  16. Gene regulatory interactions are of fundamental importance to various biological functions and processes. However, only a few previous computational studies have claimed success in revealing genome-wide regula...

    Authors: Shupeng Gui, Andrew P. Rice, Rui Chen, Liang Wu, Ji Liu and Hongyu Miao

    Citation: BMC Bioinformatics 2017 18:74

    Content type: Methodology Article

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  17. With the increase in the amount of DNA methylation and gene expression data, the epigenetic mechanisms of cancers can be extensively investigate. Available methods integrate the DNA methylation and gene expres...

    Authors: Xiaoke Ma, Zaiyi Liu, Zhongyuan Zhang, Xiaotai Huang and Wanxin Tang

    Citation: BMC Bioinformatics 2017 18:72

    Content type: Methodology Article

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  18. Mixed cultures of different microbial species are increasingly being used to carry out a specific biochemical function in lieu of engineering a single microbe to do the same task. However, knowing how differen...

    Authors: Onur Erbilgin, Benjamin P. Bowen, Suzanne M. Kosina, Stefan Jenkins, Rebecca K. Lau and Trent R. Northen

    Citation: BMC Bioinformatics 2017 18:57

    Content type: Research article

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  19. The development of large-scale kinetic models is one of the current key issues in computational systems biology and bioinformatics. Here we consider the problem of parameter estimation in nonlinear dynamic mod...

    Authors: David R. Penas, Patricia González, Jose A. Egea, Ramón Doallo and Julio R. Banga

    Citation: BMC Bioinformatics 2017 18:52

    Content type: Methodology Article

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  20. The molecular assays that test gene expression, transcriptional, and epigenetic regulation are increasingly diverse and numerous. The information generated by each type of assay individually gives an insight i...

    Authors: N. Ari Wijetunga, Andrew D. Johnston, Ryo Maekawa, Fabien Delahaye, Netha Ulahannan, Kami Kim and John M. Greally

    Citation: BMC Bioinformatics 2017 18:41

    Content type: Software

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  21. Drug-drug interactions (DDIs) are one of the major concerns in drug discovery. Accurate prediction of potential DDIs can help to reduce unexpected interactions in the entire lifecycle of drugs, and are importa...

    Authors: Wen Zhang, Yanlin Chen, Feng Liu, Fei Luo, Gang Tian and Xiaohong Li

    Citation: BMC Bioinformatics 2017 18:18

    Content type: Research article

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  22. Advances in experimental biology have enabled the collection of enormous troves of data on genomic variation in living organisms. The interpretation of this data to extract actionable information is one of the...

    Authors: Zeina Z. Shreif, Daniel M. Gatti and Vipul Periwal

    Citation: BMC Bioinformatics 2016 17:544

    Content type: Methodology Article

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  23. Networks are popular and powerful tools to describe and model biological processes. Many computational methods have been developed to infer biological networks from literature, high-throughput experiments, and...

    Authors: Francesco Iorio, Marti Bernardo-Faura, Andrea Gobbi, Thomas Cokelaer, Giuseppe Jurman and Julio Saez-Rodriguez

    Citation: BMC Bioinformatics 2016 17:542

    Content type: Methodology Article

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  24. The alignment of protein-protein interaction (PPI) networks enables us to uncover the relationships between different species, which leads to a deeper understanding of biological systems. Network alignment can...

    Authors: Ehsan Kazemi, Hamed Hassani, Matthias Grossglauser and Hassan Pezeshgi Modarres

    Citation: BMC Bioinformatics 2016 17:527

    Content type: Research Article

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  25. When modeling in Systems Biology and Systems Medicine, the data is often extensive, complex and heterogeneous. Graphs are a natural way of representing biological networks. Graph databases enable efficient sto...

    Authors: Vasundra Touré, Alexander Mazein, Dagmar Waltemath, Irina Balaur, Mansoor Saqi, Ron Henkel, Johann Pellet and Charles Auffray

    Citation: BMC Bioinformatics 2016 17:494

    Content type: Software

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  26. Gene network inference (GNI) algorithms can be used to identify sets of coordinately expressed genes, termed network modules from whole transcriptome gene expression data. The identification of such modules ha...

    Authors: Casey P. Shannon, Virginia Chen, Mandeep Takhar, Zsuzsanna Hollander, Robert Balshaw, Bruce M. McManus, Scott J. Tebbutt, Don D. Sin and Raymond T. Ng

    Citation: BMC Bioinformatics 2016 17:460

    Content type: Methodology article

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  27. Accurately prioritizing candidate disease genes is an important and challenging problem. Various network-based methods have been developed to predict potential disease genes by utilizing the disease similarity...

    Authors: Jingchao Ni, Mehmet Koyuturk, Hanghang Tong, Jonathan Haines, Rong Xu and Xiang Zhang

    Citation: BMC Bioinformatics 2016 17:453

    Content type: Research Article

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  28. Prior knowledge networks (PKNs) provide a framework for the development of computational biological models, including Boolean models of regulatory networks which are the focus of this work. PKNs are created by...

    Authors: Julien Dorier, Isaac Crespo, Anne Niknejad, Robin Liechti, Martin Ebeling and Ioannis Xenarios

    Citation: BMC Bioinformatics 2016 17:410

    Content type: Methodology article

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  29. Biological networks provide great potential to understand how cells function. Network motifs, frequent topological patterns, are key structures through which biological networks operate. Finding motifs in biol...

    Authors: Rasha Elhesha and Tamer Kahveci

    Citation: BMC Bioinformatics 2016 17:408

    Content type: Research Article

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  30. Several recent studies have used the Minimum Dominating Set (MDS) model to identify driver nodes, which provide the control of the underlying networks, in protein interaction networks. There may exist multiple...

    Authors: Xiao-Fei Zhang, Le Ou-Yang, Dao-Qing Dai, Meng-Yun Wu, Yuan Zhu and Hong Yan

    Citation: BMC Bioinformatics 2016 17:358

    Content type: Research Article

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  31. Rapid technological innovation for the generation of single-cell genomics data presents new challenges and opportunities for bioinformatics analysis. One such area lies in the development of new ways to train ...

    Authors: Chee Yee Lim, Huange Wang, Steven Woodhouse, Nir Piterman, Lorenz Wernisch, Jasmin Fisher and Berthold Göttgens

    Citation: BMC Bioinformatics 2016 17:355

    Content type: Methodology article

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  32. Network enrichment analysis is a powerful method, which allows to integrate gene enrichment analysis with the information on relationships between genes that is provided by gene networks. Existing tests for ne...

    Authors: Mirko Signorelli, Veronica Vinciotti and Ernst C. Wit

    Citation: BMC Bioinformatics 2016 17:352

    Content type: Methodology Article

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  33. The explosive growth of microbiome research has yielded great quantities of data. These data provide us with many answers, but raise just as many questions. 16S rDNA—the backbone of microbiome analyses—allows ...

    Authors: Helena Mendes-Soares, Michael Mundy, Luis Mendes Soares and Nicholas Chia

    Citation: BMC Bioinformatics 2016 17:343

    Content type: Software

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  34. Many centrality measures have been proposed to mine and characterize the correlations between network topological properties and protein essentiality. However, most of them show limited prediction accuracy, an...

    Authors: Xue Zhang, Wangxin Xiao, Marcio Luis Acencio, Ney Lemke and Xujing Wang

    Citation: BMC Bioinformatics 2016 17:322

    Content type: Methodology article

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  35. Inference of active regulatory cascades under specific molecular and environmental perturbations is a recurring task in transcriptional data analysis. Commercial tools based on large, manually curated networks...

    Authors: Carl Tony Fakhry, Parul Choudhary, Alex Gutteridge, Ben Sidders, Ping Chen, Daniel Ziemek and Kourosh Zarringhalam

    Citation: BMC Bioinformatics 2016 17:318

    Content type: Research Article

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