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A state-of-art review on the agility of quantitative proteomics in tuberculosis research

Muthu, Manikandan, Deenadayalan, Anbarasu, Ramachandran, D., Paul, Diby, Gopal, Judy, Chun, Sechul
Trends in analytical chemistry 2018 v.102 pp. 369-378
prediction, protein synthesis, proteomics, statistics, tuberculosis
Quantitative proteomics (QP) was that which moved mere qualitative proteomic data, towards that which started making sense, not just sense but statistics. QP data is essential for predicting and validating the role of differentially expressed proteins in various cellular processes and thus QP has led to a better understanding of various diseases of high significance which has been well documented in previous reviews. However, with respect to tuberculosis (TB), an assessment of the current achievements made through QP has never been reviewed. Therefore, in this review, a coherent report regarding milestones and achievements of QP in TB research is presented. Furthermore, the strengths of labeled and label free QP as successful tools in leading to a fundamental understanding of TB and the causal organism is systematically expatiated. The challenges facing the success of QP and the scope for expanding its territories to reach newer horizons are contemplated.