BioMed Research International

Big Data and Network Biology 2016


Status
Published

1Nara Institute of Science and Technology, Nara, Japan

2University of Nairobi, Nairobi, Kenya

3Bogor Agricultural University (IPB), Bogor, Indonesia


Big Data and Network Biology 2016

Description

From the beginning of the present millennium, science is going through two rapidly changing phenomena: one is that the capabilities of the computers and software tools are increasing from terabytes to petabytes and beyond and the other is the advancement in molecular biological experiments producing piles of data related to genome and RNA sequence, protein and metabolite abundance, protein-protein and protein-DNA interaction, gene expression, 3D structure of omics molecules, and so on. As a natural consequence, these two fields have become complementary to each other bridged by other branches of science, for example, statistics, mathematics, physics, and chemistry. Thus, the combination of versatile knowledge caused the advent of big data biology, network biology, and many other new subjects.

Network biology facilitates the system-level understanding of the cell or cellular components and subprocesses. Big biological data can be transformed into versatile networks, and therefore big data biology and network biology are linked to each other. In this special issue, we are calling papers on new ways to collect, store, retrieve, filter, integrate, analyze, and share biological data, novel analytical tools, and novel information extracted from big biological data and biological networks.

Potential topics include, but are not limited to:

  • Next generation sequencing for custom genomics
  • Microarray analysis and disease genomics
  • Protein-protein interaction, gene regulatory, and metabolic and signaling networks
  • Reverse engineering of metabolic networks
  • Biomarkers and drug discovery
  • Networks of drugs and diseases
  • Effects of metabolites on human health
  • Systems biology and synthetic biology
  • Chemometrics and cheminformatics
  • Omics databases and data analysis

Articles

  • Special Issue
  • - Volume 2017
  • - Article ID 9432460
  • - Editorial

Big Data and Network Biology 2016

Shigehiko Kanaya | Md. Altaf-Ul-Amin | ... | Farit Mochamad Afendi
  • Special Issue
  • - Volume 2017
  • - Article ID 6261802
  • - Research Article

MapReduce Algorithms for Inferring Gene Regulatory Networks from Time-Series Microarray Data Using an Information-Theoretic Approach

Yasser Abduallah | Turki Turki | ... | Jason T. L. Wang
  • Special Issue
  • - Volume 2017
  • - Article ID 5296729
  • - Research Article

Novel Approach to Classify Plants Based on Metabolite-Content Similarity

Kang Liu | Azian Azamimi Abdullah | ... | Shigehiko Kanaya
  • Special Issue
  • - Volume 2016
  • - Article ID 7147039
  • - Research Article

A Systematic Framework for Drug Repositioning from Integrated Omics and Drug Phenotype Profiles Using Pathway-Drug Network

Erkhembayar Jadamba | Miyoung Shin
  • Special Issue
  • - Volume 2016
  • - Article ID 3164624
  • - Research Article

Horizontally Transferred Genetic Elements in the Tsetse Fly Genome: An Alignment-Free Clustering Approach Using Batch Learning Self-Organising Map (BLSOM)

Ryo Nakao | Takashi Abe | ... | Chihiro Sugimoto
  • Special Issue
  • - Volume 2016
  • - Article ID 8313272
  • - Research Article

Correlation-Based Network Generation, Visualization, and Analysis as a Powerful Tool in Biological Studies: A Case Study in Cancer Cell Metabolism

Albert Batushansky | David Toubiana | Aaron Fait
  • Special Issue
  • - Volume 2016
  • - Article ID 3594937
  • - Research Article

Semisupervised Learning Based Disease-Symptom and Symptom-Therapeutic Substance Relation Extraction from Biomedical Literature

Qinlin Feng | Yingyi Gui | ... | Yuxia Li
BioMed Research International
 Journal metrics
Acceptance rate30%
Submission to final decision82 days
Acceptance to publication44 days
CiteScore2.410
Impact Factor2.197
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