AIMS AND SCOPE

"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.

 

Keywords/Sub-Topics:

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

13. Interaction Proteomics

• Lipidomics

15. Mass Spectrometry-Based Proteomics
16. Metabolomics-Proteomics Integration
17. Microbial Proteomics

• Multi-Omics Integration

19. Native Mass Spectrometry
20. Neuroproteomics

• Non-Model Organism Proteomics

22. Nuclear Proteomics
23. Omics Data Integration
24. Organelle Proteomics
25. Pathogen Proteomics
26. Pharmacoproteomics
27. Plant Proteomics
28. Post-Translational Modifications
29. Precision Proteomics
30. Protein Complexes and Networks
31. Protein Expression Profiling
32. Protein Folding and Dynamics
33. Protein Interactions
34. Protein Localization and Trafficking
35. Proteogenomics
36. Proteome Informatics
37. Proteome Stability and Turnover
38. Proteomics in Drug Discovery
39. Proteomics in Personalized Medicine
40. Proteomics in Translational Research

• Proteomics of Aging

42. Proteomics of Autophagy
43. Proteomics of Extracellular Vesicles
44. Proteomics of Lipids
45. Proteomics of Membrane Proteins
46. Proteomics of Mitochondria
47. Proteomics of Nucleic Acids
48. Proteomics of Organelles
49. Proteomics of Stem Cells
50. Quantitative Proteomics
51. Secretome Proteomics
52. Structural Proteomics
53. Top-Down Proteomics
54. Transcriptomics-Pro
55. Protein post-translational modifications
56. Structural proteomics
57. Systems biology and proteomics
58. Quantitative proteomics
59. High-throughput proteomics
60. Mass spectrometry-based proteomics
61. Bioinformatics and computational proteomics
62. Proteomics in drug discovery and development
63. Proteomics in personalized medicine
64. Cancer proteomics
65. Neuroproteomics
66. Cardiovascular proteomics
67. Immunoproteomics
68. Plant proteomics
69. Food proteomics
70. Environmental proteomics
71. Proteomics and microbiology
72. Single-cell proteomics
73. Spatial proteomics
74. Glycoproteomics
75. Lipidomics
76. Metabolomics
77. Multi-omics integration
78. Proteomics data analysis and interpretation
79. Quality control in proteomics
80. Proteomics standards and guidelines

• Ethics in proteomics research

82. Challenges and future directions in proteomics
83. Proteomics education and training
84. Industrial proteomics
85. Proteomics in agriculture
86. Proteomics in veterinary science
87. Proteomics in ecology and biodiversity
88. Proteomics in biotechnology
89. Proteomics in biomarker discovery
90. Proteomics in infectious diseases
91. Proteomics in autoimmune diseases
92. Proteomics in rare diseases
93. Proteomics in aging research
94. Proteomics in reproductive medicine
95. Proteomics in regenerative medicine
96. Proteomics in stem cell research
97. Proteomics in organ transplantation
98. Proteomics in sports medicine
99. Proteomics in forensic science
100. Proteomics in space research
101. Proteomics and artificial intelligence
102. Functional proteomics
103. Glycoproteomics
104. Imaging mass spectrometry
105. Immuno-proteomics
106. In-situ proteomics
107. Interactomics
108. Kinomics
109. Lipidomics
110. Metabolomics
111. Multi-omics
112. Nanoproteomics
113. Neuroproteomics
114. Omics data integration
115. Peptidomics
116. Phosphoproteomics
117. Post-translational modifications
118. Precision proteomics
119. Protein arrays
120. Protein biochemistry
121. Protein complexes
122. Protein engineering
123. Protein expression
124. Protein folding
125. Protein function
126. Protein identification
127. Protein interactions
128. Protein isolation and purification
129. Protein modifications
130. Protein networks
131. Protein quantification
132. Proteogenomics
133. Proteolysis
134. Proteomics databases
135. Proteomics software
136. Proteomics standards
137. Proteomics techniques
138. Proteomics workflows
139. Proteostasis
140. PTMomics
141. Quantitative proteomics
142. Structural biology
143. Systems biology
144. Top-down proteomics
145. Transcriptional regulation
146. Translational regulation
147. Translational proteomics
148. Tumor proteomics
149. Ubiquitinomics
150. Veterinary proteomics
151. Virus proteomics
152. Yeast proteomics
153. Bioinformatics
154. Data analysis
155. Data management
156. Data mining
157. Data visualization
158. Databases
159. Machine learning
160. Network analysis
161. Statistical analysis
162. Systems biology modeling
163. Artificial intelligence
164. Big data analytics
165. Biostatistics
166. Clinical data analysis
167. Computational biology
168. Computational chemistry
169. Computational proteomics
170. Computer-aided drug design
171. Deep learning
172. High-performance computing
173. Image analysis
174. Machine learning algorithms
175. Molecular dynamics simulation
176. Natural language processing
177. Next-generation sequencing data analysis
178. Predictive modeling
179. Proteomics data analysis
180. Quantitative data analysis
181. Software development
182. Structural bioinformatics
183. Text mining
184. Workflow development
185. Systems biology data analysis
186. Drug discovery
187. Gene regulation
188. Molecular biology
189. Structural biology
190. Systems biology
191. Transcriptional regulation
192. Translational regulation
193. Structural biology
194. Genome analysis
195. Protein engineering
196. Protein function
197. Signal transduction
198. Molecular diagnostics
199. Gene expression
200. Pharmacogenomics
201. 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.