International Journal of Genomics

Novel Computational Technologies for Next-Generation Sequencing Data Analysis and Their Applications


Status
Published

Lead Editor

1Providence University, Taichung, Taiwan

2University of Ulster, Londonderry, UK

3Chang Gung University, Taoyuan County, Taiwan

4Arkansas State University, Jonesboro, USA


Novel Computational Technologies for Next-Generation Sequencing Data Analysis and Their Applications

Description

Next generational sequencing (NGS) technologies, such as Illumina/Solexa, ABI/SOLiD, and Roche/454 Pyrosequencing, are revolutionizing the acquisition of genomic data at relatively low cost. NGS technologies are rapidly changing the approach to complex genomic studies, opening a way to the development of personalized drugs and personalized medicine. NGS technologies use massive throughput sequencing to obtain relatively short-reads. NGS technologies will generate enormous datasets, in which even small genomic projects may generate terabytes of data. Therefore, new computational methods are needed to analyze a wide range of genetic information and to assist data interpretation and downstream applications, including high-throughput polymorphism detections, comparative genomics, prediction of gene function and protein structure, transcriptome analysis, mutation detection and confirmation, genome mapping, and drug design. The creation of large-scale datasets now poses a great computational challenge. It will be imperative to improve software pipelines, so that we can analyze genome data more efficiently.

In this special issue, we attempt to focus on new algorithm approaches, original research, and software tools designed for analysis of NGS-generating data sets. Methods and experiments, demonstrating novel computing platforms, developing new models, presenting new directions for future research, are also welcome. This special issue provides an international forum for researchers to present their developments and ideas in the field, with particular emphasis on the technical and observational results obtained within the recent years.

Potential topics include, but are not limited to:

  • High performance computing technologies for NGS data analysis and applications
  • Cloud computing for next-generation sequencing techniques and applications
  • Novel approach for biomedicine development based on NGS data
  • Database technologies for analysis of NGS datasets
  • Software tools for NGS data analysis
  • Bioinformatics models, methods, and algorithms for NGS data
  • Mathematical and statistical methods for analysis of NGS data
  • Novel approaches for analysis of metagenomics generated by NGS
  • New sequencing technology for transcriptome analysis -RNA sequencing in one cell
  • NGS for environmental DNA analysis
  • NGS in aging research

Articles

  • Special Issue
  • - Volume 2015
  • - Article ID 254685
  • - Editorial

Novel Computational Technologies for Next-Generation Sequencing Data Analysis and Their Applications

Chuan Yi Tang | Che-Lun Hung | ... | Hai Jiang
  • Special Issue
  • - Volume 2015
  • - Article ID 563482
  • - Research Article

RECORD: Reference-Assisted Genome Assembly for Closely Related Genomes

Krisztian Buza | Bartek Wilczynski | Norbert Dojer
  • Special Issue
  • - Volume 2015
  • - Article ID 502795
  • - Research Article

Evaluating the Cassandra NoSQL Database Approach for Genomic Data Persistency

Rodrigo Aniceto | Rene Xavier | ... | Sérgio Lifschitz
  • Special Issue
  • - Volume 2015
  • - Article ID 761063
  • - Research Article

Accelerating Smith-Waterman Alignment for Protein Database Search Using Frequency Distance Filtration Scheme Based on CPU-GPU Collaborative System

Yu Liu | Yang Hong | ... | Che-Lun Hung
  • Special Issue
  • - Volume 2015
  • - Article ID 259320
  • - Research Article

SimpLiFiCPM: A Simple and Lightweight Filter-Based Algorithm for Circular Pattern Matching

Md. Aashikur Rahman Azim | Costas S. Iliopoulos | ... | M. Samiruzzaman
  • Special Issue
  • - Volume 2015
  • - Article ID 197895
  • - Research Article

A New Binning Method for Metagenomics by One-Dimensional Cellular Automata

Ying-Chih Lin
  • Special Issue
  • - Volume 2015
  • - Article ID 196591
  • - Research Article

Spaced Seed Data Structures for De Novo Assembly

Inanç Birol | Justin Chu | ... | René L. Warren
  • Special Issue
  • - Volume 2015
  • - Article ID 950905
  • - Research Article

Accelerating Multiple Compound Comparison Using LINGO-Based Load-Balancing Strategies on Multi-GPUs

Chun-Yuan Lin | Chung-Hung Wang | ... | Yu-Shiang Lin
International Journal of Genomics
 Journal metrics
Acceptance rate35%
Submission to final decision76 days
Acceptance to publication31 days
CiteScore3.400
Impact Factor2.414
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