LabCompass

Lijun Cheng

Biochemistry, Genetics and Molecular Biology · The Ohio State University

OpenAlex ORCID
Mid career · publishing since 2002
Bioinformatics and Genomic NetworksComputational Drug Discovery MethodsPancreatic and Hepatic Oncology ResearchCancer Genomics and DiagnosticsGene expression and cancer classification

Publications

128

Citations

5,474

Est. group size

~8

Recurring co-author estimate

Active years

25

Publishing since 2002

Research summary
AI-generated

Lijun Cheng's work focuses on using computational and genomic approaches to study cancer, including identifying gene essentiality in cancer cell death pathways, finding molecular mechanisms linking cancer to other diseases, and predicting synthetic lethality (a strategy for designing cancer drugs that kill cells only when two genes are disrupted together). The research combines bioinformatics, cancer genomics, and machine learning methods, with some publications extending into unrelated areas like image processing and agricultural technology.

Cancer genomics and gene essentialityComputational drug discovery and synthetic lethality predictionBioinformatics and gene expression analysisTranscriptomics and disease mechanism studiesMachine learning applications across domains

Publication output has been variable over the last decade, with a notable peak in 2023 followed by a decline in 2024 and partial recovery in 2025-2026.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026

Publication cadence
Publications per year over the last 10 years — averaging 8.0/year recently
2017: 9 publications172018: 12 publications182019: 9 publications192020: 13 publications202021: 9 publications212022: 10 publications222023: 19 publications19232024: 2 publications242025: 7 publications252026: 2 publications26
Recent publications
Publishes in
  • Cancer Research×11
  • PMC×6
  • Cancers×5
  • Genes×5
  • bioRxiv (Cold Spring Harbor Laboratory)×4
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By research-topic overlap
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  • Kunjie Fan

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  • Yijie Wang

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This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.

Last updated Jul 19, 2026.

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