Omics Data Integration towards Mining of Phenotype Specific Biomarkers in Cancer, Volume II

295K

views

402

authors

65

articles

Omics Data Integration towards Mining of Phenotype Specific Biomarkers in Cancer, Volume II

295K

views

402

authors

65

articles

Editors

5

Harbin Medical University

Central South University

Respiratory Medicine Unit, Department of Medicine & Centre for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden

Harbin Institute of Technology

Moffitt Cancer Center

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Following the first volume Omics Data Integration towards Mining of Phenotype Specific Biomarkers in Cancers and Diseases, we welcome researchers to contribute to this Research Topic dedicated to cancer research with articles that provide interesting insights or new biological observations including, but not limited to, the following areas in cancer:

• Machine learning approaches and applications for integrating multi-level omics data.
• Statistical methods and applications for integrating multi-level omics data.
• Identification and validation of molecular biomarker for cancers.
• Tools and databases for integrating and analysing omics data.
• Pan-cancer analysis and validation through integrating multi-level omics data.
• Novel findings on molecular biomarkers and signatures of cancers.
• Identification of novel prognostic biomarkers of cancers.

Please note: The findings based on data integration should be also validated by observational/experimental data. Descriptive studies and studies consisting solely of bioinformatic investigation of publicly available genomic/transcriptomic data do not fall within the scope of the journal.

Following the first volume Omics Data Integration towards Mining of Phenotype Specific Biomarkers in Cancers and Diseases, we welcome researchers to contribute to this Research Topic dedicated to cancer research with articles that provide interesting insights or new biological observations including, but not limited to, the following areas in cancer:

• Machine learning approaches and applications for integrating multi-level omics data.
• Statistical methods and applications for integrating multi-level omics data.
• Identification and validation of molecular biomarker for cancers.
• Tools and databases for integrating and analysing omics data.
• Pan-cancer analysis and validation through integrating multi-level omics data.
• Novel findings on molecular biomarkers and signatures of cancers.
• Identification of novel prognostic biomarkers of cancers.

Please note: The findings based on data integration should be also validated by observational/experimental data. Descriptive studies and studies consisting solely of bioinformatic investigation of publicly available genomic/transcriptomic data do not fall within the scope of the journal.

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Editors

Harbin Medical University

Central South University

Respiratory Medicine Unit, Department of Medicine & Centre for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden

Harbin Institute of Technology

Moffitt Cancer Center

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294,956 Total views

200,400 Article views

89,966 Article downloads

4,590 Topic views

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Frontiers in Cell and Developmental Biology

Molecular and Cellular Pathology

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