BioMed Research International

Bioinformatic Approaches for Fungal Omics


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Published

Lead Editor
Guest Editors

1Fudan University, Shanghai, China

2Yale University, New Haven, USA

3UT Southwestern Medical Center, Dallas, USA


Bioinformatic Approaches for Fungal Omics

Description

Fungal omics (including genomics, transcriptomics, metabolomics, proteomics, and lipidomics) are now broadly used and studied to help understand both the basic fungal biology and associated applications. Due to the advantages of the Next-Generation Sequencing (NGS) techniques, bioinformatics technology, and the relatively smaller size of fungal genomes as compared to other eukaryotes, sequencing and analysis of fungal genomics become much easier. Along with the acquisition of fungal genomic data, other omic data have been increasingly reported. Appropriate data mining of these omic data in depth and the obtained information can benefit our understanding of the complex of fungal biological processes from genotype and physiology to phenotype, including cell-cell (microbial) communications and pathogen-host interactions and beyond. 

In this special issue, we are trying to focus on the most recent studies based on fungal omics related area, including but not limited to fungal genomics, proteomics, and lipidomics. The papers focusing on all aspects of fungal omics such as fungal associated human diseases, drug developments, biomarker screenings (e.g., vaccine targets), fungal evolution, and biodiversity are all welcomed to be submitted to this issue. In particular, we welcome the developments of new bioinformatic tools (including informatics platforms) for high throughput omic data analysis.

This Special Issue is open to all related original research articles, reports as well as reviews.

Potential topics include but are not limited to the following:

  • Fungal omics
  • Bioinformatic approaches and tools developed for (fungal) omic data analysis
  • Fungal physiology and biology revealed by the omic data
  • Fungal evolution and biodiversity analysis
  • Other applications that can help interpret fungal omic data
  • Microbial omics (not limited to fungal omics) and Metagenomics

Articles

  • Special Issue
  • - Volume 2017
  • - Article ID 7270485
  • - Editorial

Bioinformatic Approaches for Fungal Omics

Guohua Xiao | Xinyu Zhang | Qiang Gao
  • Special Issue
  • - Volume 2017
  • - Article ID 6271358
  • - Research Article

Analysis of the Bacterial Communities in Two Liquors of Soy Sauce Aroma as Revealed by High-Throughput Sequencing of the 16S rRNA V4 Hypervariable Region

Jing Tang | Xiaoxin Tang | ... | Yin Yi
  • Special Issue
  • - Volume 2017
  • - Article ID 7198614
  • - Research Article

Comparison and Validation of Putative Pathogenicity-Related Genes Identified by T-DNA Insertional Mutagenesis and Microarray Expression Profiling in Magnaporthe oryzae

Ying Wang | Ying Wáng | ... | Da Peng Bao
  • Special Issue
  • - Volume 2017
  • - Article ID 9390803
  • - Research Article

Molecular Cloning, Bioinformatic Analysis, and Expression of Bombyx mori Lebocin 5 Gene Related to Beauveria bassiana Infection

Dingding Lü | Chengxiang Hou | ... | Xijie Guo
  • Special Issue
  • - Volume 2016
  • - Article ID 4841756
  • - Research Article

RNA Sequencing Reveals Xyr1 as a Transcription Factor Regulating Gene Expression beyond Carbohydrate Metabolism

Liang Ma | Ling Chen | ... | Zhihua Zhou
  • Special Issue
  • - Volume 2016
  • - Article ID 4783841
  • - Research Article

Workflow for Genome-Wide Determination of Pre-mRNA Splicing Efficiency from Yeast RNA-seq Data

Martin Převorovský | Martina Hálová | ... | Petr Folk
  • Special Issue
  • - Volume 2016
  • - Article ID 5837293
  • - Research Article

Comparative Proteomic Analysis of Light-Induced Mycelial Brown Film Formation in Lentinula edodes

Li Hua Tang | Qi Tan | ... | Ying Wang
BioMed Research International
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Acceptance rate31%
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CiteScore3.600
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