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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. The studies of functions of circular RNAs (circRNAs) are heavily focused on the regulation of gene expression through interactions with multiple miRNAs. However, the number of predicted target genes is typical...

    Authors: Ya-Chi Lin, Yueh-Chun Lee, Kai-Li Chang and Kuei-Yang Hsiao

    Citation: BMC Bioinformatics 2019 20:372

    Content type: Software

    Published on:

  2. Detection of central nodes in asymmetrically directed biological networks depends on centrality metrics quantifying individual nodes’ importance in a network. In topological analyses on metabolic networks, var...

    Authors: Eun-Youn Kim, Daniel Ashlock and Sung Ho Yoon

    Citation: BMC Bioinformatics 2019 20:328

    Content type: Research article

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  3. Host factors of influenza virus replication are often found in key topological positions within protein-protein interaction networks. This work explores how protein states can be manipulated through controllab...

    Authors: Emily E. Ackerman, John F. Alcorn, Takeshi Hase and Jason E. Shoemaker

    Citation: BMC Bioinformatics 2019 20:297

    Content type: Research article

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  4. Biochemical networks are often described through static or time-averaged measurements of the component macromolecules. Temporal variation in these components plays an important role in both describing the dyna...

    Authors: Maryam Masnadi-Shirazi, Mano R. Maurya, Gerald Pao, Eugene Ke, Inder M. Verma and Shankar Subramaniam

    Citation: BMC Bioinformatics 2019 20:294

    Content type: Research article

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  5. Although several studies have provided insights into the role of long non-coding RNAs (lncRNAs), the majority of them have unknown function. Recent evidence has shown the importance of both lncRNAs and chromat...

    Authors: Denise Thiel, Nataša Djurdjevac Conrad, Evgenia Ntini, Ria X. Peschutter, Heike Siebert and Annalisa Marsico

    Citation: BMC Bioinformatics 2019 20:292

    Content type: Methodology article

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  6. The complexity of representing biological systems is compounded by an ever-expanding body of knowledge emerging from multi-omics experiments. A number of pathway databases have facilitated pathway-centric appr...

    Authors: Daniel Domingo-Fernández, Sarah Mubeen, Josep Marín-Llaó, Charles Tapley Hoyt and Martin Hofmann-Apitius

    Citation: BMC Bioinformatics 2019 20:243

    Content type: Software

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  7. Characterizing the modular structure of cellular network is an important way to identify novel genes for targeted therapeutics. This is made possible by the rising of high-throughput technology. Unfortunately,...

    Authors: Lifan Liang, Vicky Chen, Kunju Zhu, Xiaonan Fan, Xinghua Lu and Songjian Lu

    Citation: BMC Bioinformatics 2019 20:225

    Content type: Methodology article

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  8. Gene networks in living cells can change depending on various conditions such as caused by different environments, tissue types, disease states, and development stages. Identifying the differential changes in ...

    Authors: Chen Wang, Feng Gao, Georgios B. Giannakis, Gennaro D’Urso and Xiaodong Cai

    Citation: BMC Bioinformatics 2019 20:224

    Content type: Methodology article

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  9. Over one hundred different types of post-transcriptional RNA modifications have been identified in human. Researchers discovered that RNA modifications can regulate various biological processes, and RNA methyl...

    Authors: Xiangyu Wu, Zhen Wei, Kunqi Chen, Qing Zhang, Jionglong Su, Hui Liu, Lin Zhang and Jia Meng

    Citation: BMC Bioinformatics 2019 20:223

    Content type: Research article

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  10. Cell direct reprogramming technology has been rapidly developed with its low risk of tumor risk and avoidance of ethical issues caused by stem cells, but it is still limited to specific cell types. Direct repr...

    Authors: Leijie Li, Dongxue Che, Xiaodan Wang, Peng Zhang, Siddiq Ur Rahman, Jianbang Zhao, Jiantao Yu, Shiheng Tao, Hui Lu and Mingzhi Liao

    Citation: BMC Bioinformatics 2019 20:111

    Content type: Software

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  11. The identification of prognostic genes that can distinguish the prognostic risks of cancer patients remains a significant challenge. Previous works have proven that functional gene sets were more reliable for ...

    Authors: Xiong-Hui Zhou, Xin-Yi Chu, Gang Xue, Jiang-Hui Xiong and Hong-Yu Zhang

    Citation: BMC Bioinformatics 2019 20:85

    Content type: Research article

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  12. Biomarker discovery studies have been moving the focus from a single target gene to a set of target genes. However, the number of target genes in a drug should be minimum to avoid drug side-effect or toxicity....

    Authors: Sunjoo Bang, Sangjoon Son, Sooyoung Kim and Hyunjung Shin

    Citation: BMC Bioinformatics 2019 20:74

    Content type: Methodology article

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  13. Reconstruction of protein-protein interaction networks (PPIN) has been riddled with controversy for decades. Particularly, false-negative and -positive interactions make this progress even more complicated. Al...

    Authors: Minoo Ashtiani, Payman Nickchi, Soheil Jahangiri-Tazehkand, Abdollah Safari, Mehdi Mirzaie and Mohieddin Jafari

    Citation: BMC Bioinformatics 2019 20:73

    Content type: Software

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  14. Clustering molecular network is a typical method in system biology, which is effective in predicting protein complexes or functional modules. However, few studies have realized that biological molecules are sp...

    Authors: Lixin Cheng, Pengfei Liu, Dong Wang and Kwong-Sak Leung

    Citation: BMC Bioinformatics 2019 20:23

    Content type: Methodology article

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  15. In systems biology, there is an acute need for integrative approaches in heterogeneous network mining in order to exploit the continuous flux of genomic data. Simultaneous analysis of the metabolic pathways an...

    Authors: Alexandra Zaharia, Bernard Labedan, Christine Froidevaux and Alain Denise

    Citation: BMC Bioinformatics 2019 20:19

    Content type: Methodology article

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  16. Reverse engineering approaches to infer gene regulatory networks using computational methods are of great importance to annotate gene functionality and identify hub genes. Although various statistical algorith...

    Authors: Minzhe Zhang, Qiwei Li, Donghyeon Yu, Bo Yao, Wei Guo, Yang Xie and Guanghua Xiao

    Citation: BMC Bioinformatics 2019 20:12

    Content type: Software

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  17. Predicting drug-disease interactions (DDIs) is time-consuming and expensive. Improving the accuracy of prediction results is necessary, and it is crucial to develop a novel computing technology to predict new ...

    Authors: Zhen Cui, Ying-Lian Gao, Jin-Xing Liu, Juan Wang, Junliang Shang and Ling-Yun Dai

    Citation: BMC Bioinformatics 2019 20:5

    Content type: Methodology article

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  18. Accurate gene regulatory networks can be used to explain the emergence of different phenotypes, disease mechanisms, and other biological functions. Many methods have been proposed to infer networks from gene e...

    Authors: Phan Nguyen and Rosemary Braun

    Citation: BMC Bioinformatics 2018 19:545

    Content type: Methodology article

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  19. Identifying protein complexes from protein-protein interaction (PPI) network is one of the most important tasks in proteomics. Existing computational methods try to incorporate a variety of biological evidence...

    Authors: Bo Xu, Kun Li, Wei Zheng, Xiaoxia Liu, Yijia Zhang, Zhehuan Zhao and Zengyou He

    Citation: BMC Bioinformatics 2018 19:535

    Content type: Research article

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  20. Network analyses, such as of gene co-expression networks, metabolic networks and ecological networks have become a central approach for the systems-level study of biological data. Several software packages exi...

    Authors: Deisy Morselli Gysi, Andre Voigt, Tiago de Miranda Fragoso, Eivind Almaas and Katja Nowick

    Citation: BMC Bioinformatics 2018 19:392

    Content type: Software

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  21. Protein complexes are one of the keys to deciphering the behavior of a cell system. During the past decade, most computational approaches used to identify protein complexes have been based on discovering dense...

    Authors: Xiaoxia Liu, Zhihao Yang, Shengtian Sang, Ziwei Zhou, Lei Wang, Yin Zhang, Hongfei Lin, Jian Wang and Bo Xu

    Citation: BMC Bioinformatics 2018 19:332

    Content type: Research article

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  22. Constraint-based metabolic flux analysis of knockout strategies is an efficient method to simulate the production of useful metabolites in microbes. Owing to the recent development of technologies for artifici...

    Authors: Takeyuki Tamura

    Citation: BMC Bioinformatics 2018 19:325

    Content type: Research article

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  23. Networks whose nodes have labels can seem complex. Fortunately, many have substructures that occur often (“motifs”). A societal example of a motif might be a household. Replacing such motifs by named supernode...

    Authors: Danilo Dessì, Jacopo Cirrone, Diego Reforgiato Recupero and Dennis Shasha

    Citation: BMC Bioinformatics 2018 19:318

    Content type: Software

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  24. Target identification is necessary for the comprehensive inference of the mechanism of action of a compound. The application of computational methods to predict the targets of bioactive compounds saves cost an...

    Authors: Hao Sun, Yiting Shen, Guangwen Luo, Yuepiao Cai and Zheng Xiang

    Citation: BMC Bioinformatics 2018 19:315

    Content type: Research article

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  25. Genetic epistasis is an often-overlooked area in the study of the genomics of complex traits. Genome-wide association studies are a useful tool for revealing potential causal genetic variants, but in this cont...

    Authors: Victor A. O. Carmelo, Lisette J. A. Kogelman, Majbritt Busk Madsen and Haja N. Kadarmideen

    Citation: BMC Bioinformatics 2018 19:277

    Content type: Software

    Published on:

  26. There are different and complicated associations between genes and diseases. Finding the causal associations between genes and specific diseases is still challenging. In this work we present a method to predic...

    Authors: Ryohei Eguchi, Mohammand Bozlul Karim, Pingzhao Hu, Tetsuo Sato, Naoaki Ono, Shigehiko Kanaya and Md. Altaf-Ul-Amin

    Citation: BMC Bioinformatics 2018 19:264

    Content type: Research article

    Published on:

  27. Drug-disease associations provide important information for the drug discovery. Wet experiments that identify drug-disease associations are time-consuming and expensive. However, many drug-disease associations...

    Authors: Wen Zhang, Xiang Yue, Weiran Lin, Wenjian Wu, Ruoqi Liu, Feng Huang and Feng Liu

    Citation: BMC Bioinformatics 2018 19:233

    Content type: Research article

    Published on:

  28. A fundamental fact in biology states that genes do not operate in isolation, and yet, methods that infer regulatory networks for single cell gene expression data have been slow to emerge. With single cell sequ...

    Authors: Shuonan Chen and Jessica C. Mar

    Citation: BMC Bioinformatics 2018 19:232

    Content type: Research Article

    Published on:

  29. Part of the missing heritability in Genome Wide Association Studies (GWAS) is expected to be explained by interactions between genetic variants, also called epistasis. Various statistical methods have been dev...

    Authors: Clément Chatelain, Guillermo Durand, Vincent Thuillier and Franck Augé

    Citation: BMC Bioinformatics 2018 19:231

    Content type: Research article

    Published on:

  30. Discovery of mutated driver genes is one of the primary objective for studying tumorigenesis. To discover some relatively low frequently mutated driver genes from somatic mutation data, many existing methods i...

    Authors: Jianing Xi, Minghui Wang and Ao Li

    Citation: BMC Bioinformatics 2018 19:214

    Content type: Methodology article

    Published on:

  31. Link prediction in biomedical graphs has several important applications including predicting Drug-Target Interactions (DTI), Protein-Protein Interaction (PPI) prediction and Literature-Based Discovery (LBD). I...

    Authors: Gamal Crichton, Yufan Guo, Sampo Pyysalo and Anna Korhonen

    Citation: BMC Bioinformatics 2018 19:176

    Content type: Research article

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  32. Recently, numerous laboratory studies have indicated that many microRNAs (miRNAs) are involved in and associated with human diseases and can serve as potential biomarkers and drug targets. Therefore, developin...

    Authors: Haochen Zhao, Linai Kuang, Lei Wang, Pengyao Ping, Zhanwei Xuan, Tingrui Pei and Zhelun Wu

    Citation: BMC Bioinformatics 2018 19:141

    Content type: Research article

    Published on:

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Annual Journal Metrics

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    44 days to first decision for all manuscripts
    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)
    1.626 - SCImago Journal Rank (SJR)

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