Welcome to Ma Lab

We are group of people dedicated to Bioinformatics research and service provision.

What We Do

Within the fields of bioinformatics and systems biology, we seek to apply Big-Data technologies and methods to answer questions in plant biology, specifically in studies of crop genomics and genetics.

The main research interests include:

  • Artificial intelligence (AI) and Big-Data analysis,

  • Epitranscriptome: Bioinformatics approaches and regulation mechanisms,

  • Bioinformatics-based genotype-phenotype mapping,

  • Systems biology approaches-based plant stress research.

Recent Publications

Genome optimization via virtual simulation to accelerate maize hybrid breeding

The employment of doubled-haploid (DH) technology in maize has vastly accelerated the efficiency of developing inbred lines. The …

Evolutionary implications of the RNA N6-methyladenosine methylome in plants

Epigenetic modifications play important roles in genome evolution and innovation. However, most analyses have focused on the …

Interactive Web-based Annotation of Plant MicroRNAs with iwa-miRNA

MicroRNAs (miRNAs) are important regulators of gene expression. The large-scale detection and profiling of miRNAs has accelerated with …

deepEA: a containerized web server for interactive analysis of epitranscriptome sequencing data

RNA molecules are decorated with a variety of chemical modifications, which make up an epitranscriptome that extensively regulates gene …

Projects

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GOVS

Genome optimization via virtual simulation to accelerate maize hybrid breeding

SMART

A Database for Small Molecules with Functional Implications in Plants

iwa-RNA

Interactive Web-based Annotation of Plant MicroRNAs with iwa-miRNA

deepEA

deepEA a containerized web server for interactive analysis of epitranscriptome sequencing data

deepTS

Exploring transcriptional switches from pairwise, temporal, and population RNA-Seq data using deepTS

CAFU

A bioinformatics framework for comprehensive assembly and functional annotation

DeepGS

Deep learning-based genomic selection

Epitranscriptome

Bioinformatics approaches for epitranscriptome analysis and their applications

PEA

Plant epitranscriptome analysis

PEA-m5C

Machine learning-based m5C prediction

RAP

Gene prioritization for a pre-specific function

G2P

Bioinformatics approaches for genotype-to-phenotype mapping and their applications

miRLocator

mature miRNAs predictions from pre-miRNA sequences

BigData

Artificial intelligence (AI)-based Big-data analysis approaches and their applications

mlDNA

Machine learning-based differential network analysis

RSGCC

Gini-based transcriptiome analysis

KGBassembler

Karyotype-based genome assembly for Brassicaceae species

Meet the Team

Professor, Doctoral Supervisor

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Chuang Ma

Professor, Doctoral Supervisor

Associate Professor

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Beilei Lei

Associate Professor

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Zhenyan Miao

Associate Professor

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Zhaoxue Han

Associate Professor

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Yunjia Tang

Lecturer

PhD Candidates

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Yuhong Qi

PhD Candidate

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Zhixu Qiu

PhD Candidate

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Jing Yang

PhD Candidate

Master Candidates

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Minggui Song

Master Candidate

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Chengchao Jia

Master Candidate

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Chenhua Wu

Master Candidate

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Chujun Zhang

Master Candidate

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Jiawen Zhao

Master Candidate

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Liyuan Guo

Master Candidate

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Meihua Xu

Master Candidate

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Mengmeng Yuan

Master Candidate

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Pengjun Ding

Master Candidate

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Shuang Zhao

Master Candidate

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Wen Sun

Master Candidate

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Wenyue Huang

Master Candidate

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Yanlin Ren

Master Candidate

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Yifan Bu

Master Candidate

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Yishui Han

Master Candidate

Contact

  • The Ma Laboratory · School of Life Scieces, Northwest A&F University, Yangling, Shaanxi, 712100, China
  • Room NO.2216, State Key Laboratory of Crop Stress Biology for Arid Areas
  • Gmail
  • Google Scholar
  • Github