"Forefronts of Proteome Science" is an international, peer-reviewed, open access journal that publishes original research, review articles, and short communications in all aspects of proteome science. The journal provides a platform for researchers, scientists, and clinicians to publish their work and share their ideas and findings with the scientific community worldwide.

The journal's primary aim is to publish high-quality research that advances our understanding of proteomes and their functions. The scope of the journal includes, but is not limited to, the following topics:

  • Proteomics techniques: Developments in sample preparation, protein separation, mass spectrometry, and data analysis.
  • Proteins and their functions: Identification and characterization of proteins, protein interactions, post-translational modifications, and protein dynamics.
  • Proteome profiling: Comparative proteomics, quantitative proteomics, and functional proteomics.
  • Proteomics in health and disease: Application of proteomics in biomarker discovery, disease diagnosis, drug discovery, and personalized medicine.
  • Proteomics in plant and microbial sciences: Proteomics in plant and microbial physiology, plant-microbe interactions, and microbiome studies.
  • Structural proteomics: Structural characterization of proteins and their complexes, protein-ligand interactions, and protein folding.
  • Computational proteomics: Development and application of bioinformatics tools for proteomics data analysis and modeling.

The journal welcomes original research articles, reviews, and short communications that cover any of these topics or related areas. We also welcome interdisciplinary studies that combine proteomics with other fields such as genomics, transcriptomics, metabolomics, and bioinformatics.



  1. Antibody Proteomics
  2. Bioinformatics for Proteomics
  3. Cancer Proteomics
  4. Chemical Proteomics
  5. Clinical Proteomics
  6. Comparative Proteomics
  7. Data Analysis and Bioinformatics
  8. Disease Biomarker Discovery
  9. Epigenetic Proteomics
  10. Glycoproteomics
  11. Imaging Mass Spectrometry
  • Immunopeptidomics
  1. Interaction Proteomics
  • Lipidomics
  1. Mass Spectrometry-Based Proteomics
  2. Metabolomics-Proteomics Integration
  3. Microbial Proteomics
  • Multi-Omics Integration
  1. Native Mass Spectrometry
  2. Neuroproteomics
  • Non-Model Organism Proteomics
  1. Nuclear Proteomics
  2. Omics Data Integration
  3. Organelle Proteomics
  4. Pathogen Proteomics
  5. Pharmacoproteomics
  6. Plant Proteomics
  7. Post-Translational Modifications
  8. Precision Proteomics
  9. Protein Complexes and Networks
  10. Protein Expression Profiling
  11. Protein Folding and Dynamics
  12. Protein Interactions
  13. Protein Localization and Trafficking
  14. Proteogenomics
  15. Proteome Informatics
  16. Proteome Stability and Turnover
  17. Proteomics in Drug Discovery
  18. Proteomics in Personalized Medicine
  19. Proteomics in Translational Research
  • Proteomics of Aging
  1. Proteomics of Autophagy
  2. Proteomics of Extracellular Vesicles
  3. Proteomics of Lipids
  4. Proteomics of Membrane Proteins
  5. Proteomics of Mitochondria
  6. Proteomics of Nucleic Acids
  7. Proteomics of Organelles
  8. Proteomics of Stem Cells
  9. Quantitative Proteomics
  10. Secretome Proteomics
  11. Structural Proteomics
  12. Top-Down Proteomics
  13. Transcriptomics-Pro
  14. Protein post-translational modifications
  15. Structural proteomics
  16. Systems biology and proteomics
  17. Quantitative proteomics
  18. High-throughput proteomics
  19. Mass spectrometry-based proteomics
  20. Bioinformatics and computational proteomics
  21. Proteomics in drug discovery and development
  22. Proteomics in personalized medicine
  23. Cancer proteomics
  24. Neuroproteomics
  25. Cardiovascular proteomics
  26. Immunoproteomics
  27. Plant proteomics
  28. Food proteomics
  29. Environmental proteomics
  30. Proteomics and microbiology
  31. Single-cell proteomics
  32. Spatial proteomics
  33. Glycoproteomics
  34. Lipidomics
  35. Metabolomics
  36. Multi-omics integration
  37. Proteomics data analysis and interpretation
  38. Quality control in proteomics
  39. Proteomics standards and guidelines
  • Ethics in proteomics research
  1. Challenges and future directions in proteomics
  2. Proteomics education and training
  3. Industrial proteomics
  4. Proteomics in agriculture
  5. Proteomics in veterinary science
  6. Proteomics in ecology and biodiversity
  7. Proteomics in biotechnology
  8. Proteomics in biomarker discovery
  9. Proteomics in infectious diseases
  10. Proteomics in autoimmune diseases
  11. Proteomics in rare diseases
  12. Proteomics in aging research
  13. Proteomics in reproductive medicine
  14. Proteomics in regenerative medicine
  15. Proteomics in stem cell research
  16. Proteomics in organ transplantation
  17. Proteomics in sports medicine
  18. Proteomics in forensic science
  19. Proteomics in space research
  20. Proteomics and artificial intelligence
  21. Functional proteomics
  22. Glycoproteomics
  23. Imaging mass spectrometry
  24. Immuno-proteomics
  25. In-situ proteomics
  26. Interactomics
  27. Kinomics
  28. Lipidomics
  29. Metabolomics
  30. Multi-omics
  31. Nanoproteomics
  32. Neuroproteomics
  33. Omics data integration
  34. Peptidomics
  35. Phosphoproteomics
  36. Post-translational modifications
  37. Precision proteomics
  38. Protein arrays
  39. Protein biochemistry
  40. Protein complexes
  41. Protein engineering
  42. Protein expression
  43. Protein folding
  44. Protein function
  45. Protein identification
  46. Protein interactions
  47. Protein isolation and purification
  48. Protein modifications
  49. Protein networks
  50. Protein quantification
  51. Proteogenomics
  52. Proteolysis
  53. Proteomics databases
  54. Proteomics software
  55. Proteomics standards
  56. Proteomics techniques
  57. Proteomics workflows
  58. Proteostasis
  59. PTMomics
  60. Quantitative proteomics
  61. Structural biology
  62. Systems biology
  63. Top-down proteomics
  64. Transcriptional regulation
  65. Translational regulation
  66. Translational proteomics
  67. Tumor proteomics
  68. Ubiquitinomics
  69. Veterinary proteomics
  70. Virus proteomics
  71. Yeast proteomics
  72. Bioinformatics
  73. Data analysis
  74. Data management
  75. Data mining
  76. Data visualization
  77. Databases
  78. Machine learning
  79. Network analysis
  80. Statistical analysis
  81. Systems biology modeling
  82. Artificial intelligence
  83. Big data analytics
  84. Biostatistics
  85. Clinical data analysis
  86. Computational biology
  87. Computational chemistry
  88. Computational proteomics
  89. Computer-aided drug design
  90. Deep learning
  91. High-performance computing
  92. Image analysis
  93. Machine learning algorithms
  94. Molecular dynamics simulation
  95. Natural language processing
  96. Next-generation sequencing data analysis
  97. Predictive modeling
  98. Proteomics data analysis
  99. Quantitative data analysis
  100. Software development
  101. Structural bioinformatics
  102. Text mining
  103. Workflow development
  104. Systems biology data analysis
  105. Drug discovery
  106. Gene regulation
  107. Molecular biology
  108. Structural biology
  109. Systems biology
  110. Transcriptional regulation
  111. Translational regulation
  112. Structural biology
  113. Genome analysis
  114. Protein engineering
  115. Protein function
  116. Signal transduction
  117. Molecular diagnostics
  118. Gene expression
  119. Pharmacogenomics
  120. Pathway analysis

These keywords and sub-topics reflect the broad scope of the journal, which seeks to publish cutting-edge research in all areas of proteomics and related fields. By providing a platform for researchers to share their findings and ideas, Forefronts of Proteome Science aims to advance the field and promote the development of new technologies and applications.

The journal "Forefronts of Proteome Science" aims to publish high-quality research in the field of proteomics, with a focus on innovative and interdisciplinary approaches to the study of proteins and their interactions. The journal's mission is to advance knowledge in this rapidly evolving field and to promote collaboration and communication among researchers, clinicians, and other stakeholders. Its vision is to be a leading platform for the dissemination of cutting-edge research in proteomics, facilitating the translation of this research into clinical applications and contributing to the development of new therapeutics and diagnostics. The journal's scope encompasses all aspects of proteomics, including protein identification and characterization, post-translational modifications, protein interactions, structural biology, and proteomic data analysis. It also covers applications of proteomics in various fields, including cancer research, neurodegenerative diseases, infectious diseases, and personalized medicine. With its commitment to open access and rigorous peer review, "Forefronts of Proteome Science" provides a valuable resource for the proteomics community and promotes the translation of proteomic research into clinical practice.