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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.

Page 5 of 10

  1. With the ever increasing use of computational models in the biosciences, the need to share models and reproduce the results of published studies efficiently and easily is becoming more important. To this end, ...

    Authors: Frank T Bergmann, Richard Adams, Stuart Moodie, Jonathan Cooper, Mihai Glont, Martin Golebiewski, Michael Hucka, Camille Laibe, Andrew K Miller, David P Nickerson, Brett G Olivier, Nicolas Rodriguez, Herbert M Sauro, Martin Scharm, Stian Soiland-Reyes, Dagmar Waltemath…

    Citation: BMC Bioinformatics 2014 15:369

    Content type: Software

    Published on:

  2. Our knowledge of global protein-protein interaction (PPI) networks in complex organisms such as humans is hindered by technical limitations of current methods.

    Authors: Andrew Schoenrock, Bahram Samanfar, Sylvain Pitre, Mohsen Hooshyar, Ke Jin, Charles A Phillips, Hui Wang, Sadhna Phanse, Katayoun Omidi, Yuan Gui, Md Alamgir, Alex Wong, Fredrik Barrenäs, Mohan Babu, Mikael Benson, Michael A Langston…

    Citation: BMC Bioinformatics 2014 15:383

    Content type: Research article

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  3. Predication of gene regularity network (GRN) from expression data is a challenging task. There are many methods that have been developed to address this challenge ranging from supervised to unsupervised method...

    Authors: Zeeshan Gillani, Muhammad Sajid Hamid Akash, MD Matiur Rahaman and Ming Chen

    Citation: BMC Bioinformatics 2014 15:395

    Content type: Research article

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  4. Respiratory epithelial cells are the primary target of influenza virus infection in human. However, the molecular mechanisms of airway epithelial cell responses to viral infection are not fully understood. Rev...

    Authors: Zhi-Ping Liu, Hulin Wu, Jian Zhu and Hongyu Miao

    Citation: BMC Bioinformatics 2014 15:336

    Content type: Methodology article

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  5. Proteins dynamically interact with each other to perform their biological functions. The dynamic operations of protein interaction networks (PPI) are also reflected in the dynamic formations of protein complex...

    Authors: Le Ou-Yang, Dao-Qing Dai, Xiao-Li Li, Min Wu, Xiao-Fei Zhang and Peng Yang

    Citation: BMC Bioinformatics 2014 15:335

    Content type: Research article

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  6. Metabolic networks are represented by the set of metabolic pathways. Metabolic pathways are a series of biochemical reactions, in which the product (output) from one reaction serves as the substrate (input) to...

    Authors: Abiel Roche-Lima, Michael Domaratzki and Brian Fristensky

    Citation: BMC Bioinformatics 2014 15:318

    Content type: Research article

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  7. Prioritizing genetic variants is a challenge because disease susceptibility loci are often located in genes of unknown function or the relationship with the corresponding phenotype is unclear. A global data-mi...

    Authors: Li Jiang, Stefan M Edwards, Bo Thomsen, Christopher T Workman, Bernt Guldbrandtsen and Peter Sørensen

    Citation: BMC Bioinformatics 2014 15:315

    Content type: Research article

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  8. In somatic cancer genomes, delineating genuine driver mutations against a background of multiple passenger events is a challenging task. The difficulty of determining function from sequence data and the low fr...

    Authors: Simon Kebede Merid, Daria Goranskaya and Andrey Alexeyenko

    Citation: BMC Bioinformatics 2014 15:308

    Content type: Methodology article

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  9. Understanding the relationship between diseases based on the underlying biological mechanisms is one of the greatest challenges in modern biology and medicine. Exploring disease-disease associations by using s...

    Authors: Kai Sun, Joana P Gonçalves, Chris Larminie and Nataša Pržulj

    Citation: BMC Bioinformatics 2014 15:304

    Content type: Research article

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  10. Time series models can play an important role in disease prediction. Incidence data can be used to predict the future occurrence of disease events. Developments in modeling approaches provide an opportunity to...

    Authors: Michael J Kane, Natalie Price, Matthew Scotch and Peter Rabinowitz

    Citation: BMC Bioinformatics 2014 15:276

    Content type: Methodology article

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  11. High-throughput measurement technologies such as microarrays provide complex datasets reflecting mechanisms perturbed in an experiment, typically a treatment vs. control design. Analysis of these information r...

    Authors: Florian Martin, Alain Sewer, Marja Talikka, Yang Xiang, Julia Hoeng and Manuel C Peitsch

    Citation: BMC Bioinformatics 2014 15:238

    Content type: Methodology article

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  12. Knockdown or overexpression of genes is widely used to identify genes that play important roles in many aspects of cellular functions and phenotypes. Because next-generation sequencing generates high-throughpu...

    Authors: Reiji Teramoto, Chiaki Saito and Shin-ichi Funahashi

    Citation: BMC Bioinformatics 2014 15:228

    Content type: Methodology article

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  13. Flux Balance Analysis (FBA) is a genome-scale computational technique for modeling the steady-state fluxes of an organism’s reaction network. When the organism’s reaction network needs to be completed to obtai...

    Authors: Mario Latendresse

    Citation: BMC Bioinformatics 2014 15:225

    Content type: Research article

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  14. A key problem in the analysis of mathematical models of molecular networks is the determination of their steady states. The present paper addresses this problem for Boolean network models, an increasingly popu...

    Authors: Alan Veliz-Cuba, Boris Aguilar, Franziska Hinkelmann and Reinhard Laubenbacher

    Citation: BMC Bioinformatics 2014 15:221

    Content type: Methodology article

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  15. Identification of protein complexes can help us get a better understanding of cellular mechanism. With the increasing availability of large-scale protein-protein interaction (PPI) data, numerous computational ...

    Authors: Xiao-Fei Zhang, Dao-Qing Dai, Le Ou-Yang and Hong Yan

    Citation: BMC Bioinformatics 2014 15:186

    Content type: Research article

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  16. Networks of interacting genes and gene products mediate most cellular and developmental processes. High throughput screening methods combined with literature curation are identifying many of the protein-protei...

    Authors: Thilakam Murali, Svetlana Pacifico and Russell L Finley Jr

    Citation: BMC Bioinformatics 2014 15:177

    Content type: Research article

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  17. Optimization is the key to solving many problems in computational biology. Global optimization methods, which provide a robust methodology, and metaheuristics in particular have proven to be the most efficient...

    Authors: Jose A Egea, David Henriques, Thomas Cokelaer, Alejandro F Villaverde, Aidan MacNamara, Diana-Patricia Danciu, Julio R Banga and Julio Saez-Rodriguez

    Citation: BMC Bioinformatics 2014 15:136

    Content type: Software

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  18. Protein–protein interactions can be seen as a hierarchical process occurring at three related levels: proteins bind by means of specific domains, which in turn form interfaces through patches of residues. Detaile...

    Authors: Claudio Saccà, Stefano Teso, Michelangelo Diligenti and Andrea Passerini

    Citation: BMC Bioinformatics 2014 15:103

    Content type: Methodology article

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  19. Discovering novel interactions between HIV-1 and human proteins would greatly contribute to different areas of HIV research. Identification of such interactions leads to a greater insight into drug target pred...

    Authors: Anirban Mukhopadhyay, Sumanta Ray and Ujjwal Maulik

    Citation: BMC Bioinformatics 2014 15:26

    Content type: Methodology article

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  20. Differential gene expression (DGE) analysis is commonly used to reveal the deregulated molecular mechanisms of complex diseases. However, traditional DGE analysis (e.g., the t test or the rank sum test) tests ...

    Authors: Chao Wu, Jun Zhu and Xuegong Zhang

    Citation: BMC Bioinformatics 2013 14:365

    Content type: Methodology article

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  21. Boolean models are increasingly used to study biological signaling networks. In a Boolean network, nodes represent biological entities such as genes, proteins or protein complexes, and edges indicate activatin...

    Authors: Nikolaos Berntenis and Martin Ebeling

    Citation: BMC Bioinformatics 2013 14:361

    Content type: Software

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  22. Constrained minimal cut sets (cMCSs) have recently been introduced as a framework to enumerate minimal genetic intervention strategies for targeted optimization of metabolic networks. Two different algorithmic...

    Authors: Christian Jungreuthmayer, Govind Nair, Steffen Klamt and Jürgen Zanghellini

    Citation: BMC Bioinformatics 2013 14:318

    Content type: Methodology article

    Published on:

  23. Stochastic modeling and simulation provide powerful predictive methods for the intrinsic understanding of fundamental mechanisms in complex biochemical networks. Typically, such mathematical models involve net...

    Authors: Yannis Pantazis, Markos A Katsoulakis and Dionisios G Vlachos

    Citation: BMC Bioinformatics 2013 14:311

    Content type: Methodology article

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  24. Dendritic spines serve as key computational structures in brain plasticity. Much remains to be learned about their spatial and temporal distribution among neurons. Our aim in this study was to perform explorat...

    Authors: Aruna Jammalamadaka, Sourav Banerjee, Bangalore S Manjunath and Kenneth S Kosik

    Citation: BMC Bioinformatics 2013 14:287

    Content type: Research article

    Published on:

  25. High-throughput RNA sequencing (RNA-Seq) is a revolutionary technique to study the transcriptome of a cell under various conditions at a systems level. Despite the wide application of RNA-Seq techniques to gen...

    Authors: Mingzhu Zhu, Jeremy L Dahmen, Gary Stacey and Jianlin Cheng

    Citation: BMC Bioinformatics 2013 14:278

    Content type: Research article

    Published on:

  26. Gene regulatory network inference remains a challenging problem in systems biology despite the numerous approaches that have been proposed. When substantial knowledge on a gene regulatory network is already av...

    Authors: Céline Brouard, Christel Vrain, Julie Dubois, David Castel, Marie-Anne Debily and Florence d’Alché-Buc

    Citation: BMC Bioinformatics 2013 14:273

    Content type: Research article

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  27. Pathway analysis based on Genome-Wide Association Studies (GWAS) data has become popular as a secondary analysis strategy. Although many pathway analysis tools have been developed for case-control studies, the...

    Authors: Yo Son Park, Michael Schmidt, Eden R Martin, Margaret A Pericak-Vance and Ren-Hua Chung

    Citation: BMC Bioinformatics 2013 14:267

    Content type: Software

    Published on:

  28. The success of targeted anti-cancer drugs are frequently hindered by the lack of knowledge of the individual pathway of the patient and the extreme data requirements on the estimation of the personalized genet...

    Authors: Noah Berlow, Lara E Davis, Emma L Cantor, Bernard Séguin, Charles Keller and Ranadip Pal

    Citation: BMC Bioinformatics 2013 14:239

    Content type: Research article

    Published on:

  29. Constant technological advances have allowed scientists in biology to migrate from conventional single-omics to multi-omics experimental approaches, challenging bioinformatics to bridge this multi-tiered infor...

    Authors: Panagiotis Moulos, Julie Klein, Simon Jupp, Robert Stevens, Jean-Loup Bascands and Joost P Schanstra

    Citation: BMC Bioinformatics 2013 14:235

    Content type: Software

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  30. Mechanistic biosimulation can be used in drug development to form testable hypotheses, develop predictions of efficacy before clinical trial results are available, and elucidate clinical response to therapy. H...

    Authors: Brian J Schmidt, Fergal P Casey, Thomas Paterson and Jason R Chan

    Citation: BMC Bioinformatics 2013 14:221

    Content type: Research article

    Published on:

  31. Biomolecular pathways and networks are dynamic and complex, and the perturbations to them which cause disease are often multiple, heterogeneous and contingent. Pathway and network visualizations, rendered on a...

    Authors: Paul T Shannon, Mark Grimes, Burak Kutlu, Jan J Bot and David J Galas

    Citation: BMC Bioinformatics 2013 14:217

    Content type: Software

    Published on:

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Annual Journal Metrics

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    163 days from submission to acceptance
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    Citation Impact
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    3.213 - 5-year Impact Factor
    1.156 - Source Normalized Impact per Paper (SNIP)
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