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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. 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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  2. 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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  3. 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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  4. 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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  5. 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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  6. 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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  7. 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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  8. 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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  9. 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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  10. 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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  11. Sparse Gaussian graphical models are popular for inferring biological networks, such as gene regulatory networks. In this paper, we investigate the consistency of these models across different data platforms, ...

    Authors: Veronica Vinciotti, Ernst C. Wit, Rick Jansen, Eco J. C. N. de Geus, Brenda W. J. H. Penninx, Dorret I. Boomsma and Peter A. C. ’t Hoen

    Citation: BMC Bioinformatics 2016 17:254

    Content type: Methodology Article

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  12. Phenomics is a field in functional genomics that records variation in organismal phenotypes in the genetic, epigenetic or environmental context at a massive scale. For microbes, the key phenotype is the growth...

    Authors: Luciano Fernandez-Ricaud, Olga Kourtchenko, Martin Zackrisson, Jonas Warringer and Anders Blomberg

    Citation: BMC Bioinformatics 2016 17:249

    Content type: Software

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  13. The targeting of disease-related proteins is important for drug discovery, and yet target-based discovery has not been fruitful. Contextualizing overall biological processes is critical to formulating successf...

    Authors: Naiem T. Issa, Jordan Kruger, Henri Wathieu, Rajarajan Raja, Stephen W. Byers and Sivanesan Dakshanamurthy

    Citation: BMC Bioinformatics 2016 17:202

    Content type: Research article

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  14. We have previously presented a formal language for describing population dynamics based on environment-dependent Stochastic Tree Grammars (eSTG). The language captures in broad terms the effect of the changing...

    Authors: Adam Spiro and Ehud Shapiro

    Citation: BMC Bioinformatics 2016 17:187

    Content type: Software

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    The Erratum to this article has been published in BMC Bioinformatics 2016 17:303

  15. Recently, high-throughput experimental techniques have generated a large amount of protein-protein interaction (PPI) data which can construct large complex PPI networks for numerous organisms. System biology a...

    Authors: Yijia Zhang, Hongfei Lin, Zhihao Yang and Jian Wang

    Citation: BMC Bioinformatics 2016 17:186

    Content type: Research article

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  16. Network visualization and analysis tools aid in better understanding of complex biological systems. Furthermore, to understand the differences in behaviour of system(s) under various environmental conditions (...

    Authors: Bhusan K. Kuntal, Anirban Dutta and Sharmila S. Mande

    Citation: BMC Bioinformatics 2016 17:185

    Content type: Software

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    The Correction to this article has been published in BMC Bioinformatics 2019 20:600

  17. Biological research increasingly relies on network models to study complex phenomena. Signal Transduction Pathways are molecular circuits that model how cells receive, process, and respond to information from ...

    Authors: Gianfranco Politano, Francesca Orso, Monica Raimo, Alfredo Benso, Alessandro Savino, Daniela Taverna and Stefano Di Carlo

    Citation: BMC Bioinformatics 2016 17:157

    Content type: Software

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  18. Interoperability between formats is a recurring problem in systems biology research. Many tools have been developed to convert computational models from one format to another. However, they have been developed...

    Authors: Nicolas Rodriguez, Jean-Baptiste Pettit, Piero Dalle Pezze, Lu Li, Arnaud Henry, Martijn P. van Iersel, Gael Jalowicki, Martina Kutmon, Kedar N. Natarajan, David Tolnay, Melanie I. Stefan, Chris T. Evelo and Nicolas Le Novère

    Citation: BMC Bioinformatics 2016 17:154

    Content type: Software

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  19. Multilayered hierarchical gene regulatory networks (ML-hGRNs) are very important for understanding genetics regulation of biological pathways. However, there are currently no computational algorithms available...

    Authors: Sapna Kumari, Wenping Deng, Chathura Gunasekara, Vincent Chiang, Huann-sheng Chen, Hao Ma, Xin Davis and Hairong Wei

    Citation: BMC Bioinformatics 2016 17:132

    Content type: Methodology article

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  20. It is generally acknowledged that a functional understanding of a biological system can only be obtained by an understanding of the collective of molecular interactions in form of biological networks. Protein ...

    Authors: Shailesh Tripathi, Salissou Moutari, Matthias Dehmer and Frank Emmert-Streib

    Citation: BMC Bioinformatics 2016 17:129

    Content type: Research Article

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  21. Networks or graphs play an important role in the biological sciences. Protein interaction networks and metabolic networks support the understanding of basic cellular mechanisms. In the human brain, networks of...

    Authors: Klaus Hahn, Peter R. Massopust and Sergei Prigarin

    Citation: BMC Bioinformatics 2016 17:87

    Content type: Methodology Article

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  22. Complex disease is largely determined by a number of biomolecules interwoven into networks, rather than a single biomolecule. A key but inadequately addressed issue is how to test possible differences of the n...

    Authors: Jiadong Ji, Zhongshang Yuan, Xiaoshuai Zhang and Fuzhong Xue

    Citation: BMC Bioinformatics 2016 17:86

    Content type: Methodology article

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  23. Dynamical models of gene regulatory networks (GRNs) are highly effective in describing complex biological phenomena and processes, such as cell differentiation and cancer development. Yet, the topological and ...

    Authors: Andrea Paroni, Alex Graudenzi, Giulio Caravagna, Chiara Damiani, Giancarlo Mauri and Marco Antoniotti

    Citation: BMC Bioinformatics 2016 17:64

    Content type: Software

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  24. Inflammatory bowel disease (IBD) consists of two main disease-subtypes, Crohn’s disease (CD) and ulcerative colitis (UC); these subtypes share overlapping genetic and clinical features. Genome-wide microarray ...

    Authors: Daniele Muraro and Alison Simmons

    Citation: BMC Bioinformatics 2016 17:42

    Content type: Research Article

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  25. Gene co-expression evidenced as a response to environmental changes has shown that transcriptional activity is coordinated, which pinpoints the role of transcriptional regulatory networks (TRNs). Nevertheless,...

    Authors: Vicente Acuña, Andrés Aravena, Carito Guziolowski, Damien Eveillard, Anne Siegel and Alejandro Maass

    Citation: BMC Bioinformatics 2016 17:35

    Content type: Research Article

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  26. Differential networks have recently been introduced as a powerful way to study the dynamic rewiring capabilities of an interactome in response to changing environmental conditions or stimuli. Currently, such d...

    Authors: Sofie Van Landeghem, Thomas Van Parys, Marieke Dubois, Dirk Inzé and Yves Van de Peer

    Citation: BMC Bioinformatics 2016 17:18

    Content type: Research Article

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  27. Advances in high throughput technologies and growth of biomedical knowledge have contributed to an exponential increase in associative data. These data can be represented in the form of complex networks of bio...

    Authors: Ákos Tényi, Pedro de Atauri, David Gomez-Cabrero, Isaac Cano, Kim Clarke, Francesco Falciani, Marta Cascante, Josep Roca and Dieter Maier

    Citation: BMC Bioinformatics 2016 17:17

    Content type: Methodology article

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  28. Inferring gene regulatory network (GRN) has been an important topic in Bioinformatics. Many computational methods infer the GRN from high-throughput expression data. Due to the presence of time delays in the r...

    Authors: Leung-Yau Lo, Man-Leung Wong, Kin-Hong Lee and Kwong-Sak Leung

    Citation: BMC Bioinformatics 2015 16:395

    Content type: Research Article

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  29. Inferring gene networks from high-throughput data constitutes an important step in the discovery of relevant regulatory relationships in organism cells. Despite the large number of available Gene Regulatory Ne...

    Authors: Aurélie Pirayre, Camille Couprie, Frédérique Bidard, Laurent Duval and Jean-Christophe Pesquet

    Citation: BMC Bioinformatics 2015 16:368

    Content type: Research Article

    Published on:

  30. Network component analysis (NCA) became a popular tool to understand complex regulatory networks. The method uses high-throughput gene expression data and a priori topology to reconstruct transcription factor ...

    Authors: Naresh Doni Jayavelu, Lasse S. Aasgaard and Nadav Bar

    Citation: BMC Bioinformatics 2015 16:366

    Content type: Methodology Article

    Published on:

  31. Enrichment analysis is a popular approach to identify pathways or sets of genes which are significantly enriched in the context of differentially expressed genes. The traditional gene set enrichment approach c...

    Authors: Michaela Bayerlová, Klaus Jung, Frank Kramer, Florian Klemm, Annalen Bleckmann and Tim Beißbarth

    Citation: BMC Bioinformatics 2015 16:334

    Content type: Research article

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  32. In the field of network science, exploring principal and crucial modules or communities is critical in the deduction of relationships and organization of complex networks. This approach expands an arena, and t...

    Authors: Mohieddin Jafari, Mehdi Mirzaie and Mehdi Sadeghi

    Citation: BMC Bioinformatics 2015 16:319

    Content type: Research article

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  33. In the last decade, a great number of methods for reconstructing gene regulatory networks from expression data have been proposed. However, very few tools and datasets allow to evaluate accurately and reproduc...

    Authors: Pau Bellot, Catharina Olsen, Philippe Salembier, Albert Oliveras-Vergés and Patrick E. Meyer

    Citation: BMC Bioinformatics 2015 16:312

    Content type: Software

    Published on:

  34. The inference of complex networks from data is a challenging problem in biological sciences, as well as in a wide range of disciplines such as chemistry, technology, economics, or sociology. The quantity and q...

    Authors: Abel Folch-Fortuny, Alejandro F. Villaverde, Alberto Ferrer and Julio R. Banga

    Citation: BMC Bioinformatics 2015 16:283

    Content type: Methodology Article

    Published on:

  35. The cascade computer model (CCM) was designed as a machine-learning feature platform for prediction of drug diffusivity from the mucoadhesive formulations. Three basic models (the statistical regression model,...

    Authors: Yugyung Lee, Alok Khemka, Gayathri Acharya, Namita Giri and Chi H. Lee

    Citation: BMC Bioinformatics 2015 16:263

    Content type: Research article

    Published on:

  36. The concept of Petri nets (PN) is widely used in systems biology and allows modeling of complex biochemical systems like metabolic systems, signal transduction pathways, and gene expression networks. In partic...

    Authors: Pavel Balazki, Klaus Lindauer, Jens Einloft, Jörg Ackermann and Ina Koch

    Citation: BMC Bioinformatics 2015 16:215

    Content type: Software

    Published on:

    The Erratum to this article has been published in BMC Bioinformatics 2015 16:371

  37. Tandem repetition of structural motifs in proteins is frequently observed across all forms of life. Topology of repeating unit and its frequency of occurrence are associated to a wide range of structural and f...

    Authors: Broto Chakrabarty and Nita Parekh

    Citation: BMC Bioinformatics 2014 15:6599

    Content type: Methodology article

    Published on:

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