BioMed Research International

Advanced Computational Approaches for Medical Genetics and Genomics


Status
Published

1New Jersey Institute of Technology, Newark, USA

2The Center for Applied Genomics, Philadelphia, USA

3The University of Hong Kong, Hong Kong

4University of Southern California, Los Angeles, USA


Advanced Computational Approaches for Medical Genetics and Genomics

Description

Remarkable advances have been made in genetics and genomics over the last decade due to the rapid technology innovation in microarray and sequencing. As a result of biomedical discoveries, it is feasible to improve the diagnosis and treatment by genetic and genomic test, paving the way for an era of personalized medicine in health care. However, it remains a challenge to identify the small mutations from massive amounts of genomic data. There is an unprecedented demand for novel computational methods and analytical strategies to improve genome alignment, genome assembly, variants identification, genotype calling and association tests, etc.

This special issue aims to encourage and publish applications of innovative analysis pipelines and algorithms to find the accurate resolution of complex genetic and genomic problems in a time efficient manner. We look for high-quality papers that contribute to diagnosis and management of human disorders.

Potential topics include, but are not limited to:

  • Algorithms, software tools, and pipelines for NGS analysis and annotation
  • Algorithms, software tools, and pipelines for GWAS and CNV analysis and annotation
  • Algorithms and software tools for predicting the phenotypic impacts and therapeutically impacts of genomic variation
  • Algorithms, software tools, and studies for exploring actionable information extracted from personal genomes/exome data sets
  • Biological network and pathway analysis on cancer and other complex diseases
  • Discovery of mutations in Mendelian diseases
  • Discovery of biomarkers from genomics data

Articles

  • Special Issue
  • - Volume 2015
  • - Article ID 705469
  • - Editorial

Advanced Computational Approaches for Medical Genetics and Genomics

Zhi Wei | Xiao Chang | Junwen Wang
  • Special Issue
  • - Volume 2015
  • - Article ID 685303
  • - Research Article

Identification of Gene Biomarkers for Distinguishing Small-Cell Lung Cancer from Non-Small-Cell Lung Cancer Using a Network-Based Approach

Fei Long | Jia-Hang Su | ... | Shu-Juan Jiang
  • Special Issue
  • - Volume 2015
  • - Article ID 619730
  • - Research Article

Network-Based Association Study of Obesity and Type 2 Diabetes with Gene Expression Profiles

Siyi Zhang | Bo Wang | ... | Jing Li
  • Special Issue
  • - Volume 2015
  • - Article ID 316735
  • - Research Article

Gene Coexpression and Evolutionary Conservation Analysis of the Human Preimplantation Embryos

Tiancheng Liu | Lin Yu | ... | Yixue Li
  • Special Issue
  • - Volume 2015
  • - Article ID 901303
  • - Research Article

Deciphering the Correlation between Breast Tumor Samples and Cell Lines by Integrating Copy Number Changes and Gene Expression Profiles

Yi Sun | Qi Liu
  • Special Issue
  • - Volume 2015
  • - Article ID 319797
  • - Research Article

FARMS: A New Algorithm for Variable Selection

Susana Perez-Alvarez | Guadalupe Gómez | Christian Brander
  • Special Issue
  • - Volume 2015
  • - Article ID 205247
  • - Research Article

Network Comparison of Inflammation in Colorectal Cancer and Alzheimer’s Disease

Sungjin Park | Seok Jong Yu | ... | Seungyoon Nam
  • Special Issue
  • - Volume 2015
  • - Article ID 573956
  • - Research Article

Low-Rank and Sparse Matrix Decomposition for Genetic Interaction Data

Yishu Wang | Dejie Yang | Minghua Deng
  • Special Issue
  • - Volume 2015
  • - Article ID 483726
  • - Research Article

Statistical Genomic Approach Identifies Association between FSHR Polymorphisms and Polycystic Ovary Morphology in Women with Polycystic Ovary Syndrome

Tao Du | Yu Duan | ... | Dongzi Yang
  • Special Issue
  • - Volume 2015
  • - Article ID 143712
  • - Review Article

The Current and Future Use of Ridge Regression for Prediction in Quantitative Genetics

Ronald de Vlaming | Patrick J. F. Groenen
BioMed Research International
 Journal metrics
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Acceptance rate8%
Submission to final decision110 days
Acceptance to publication24 days
CiteScore5.300
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Impact Factor-
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