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Dr Animesh Acharjee

Departments and Institutes

Department of Biochemistry:
Visiting Scientist

Research Interests

Data driven decision making strategies which includes in the field of health care, finance, marketing domain. More specifically, high dimensional data analysis, predictive modelling, network analytics, feature selection

Keywords

Machine Learning ; Big Data Analytics ; Analytics ; Bioinformatics ; Translational medicine ; Big Data in Biology ; Statistical Learning ; Predictive Analytics

Key Publications

Murfitt SA, Zaccone P, Wang X, Acharjee A, Sawyer Y, Koulman A, Roberts LD,
Cooke A, Griffin J. A metabolomics and lipidomics study of mouse models of type 1 diabetes highlights divergent metabolism in purine and tryptophan metabolism
prior to disease on-set. J Proteome Res. 2017 Oct 10

The translation of lipid profiles to nutritional biomarkers in the study of infant metabolism. Metabolomics. Acharjee et al., 2017;13(3):25

Integration of metabolomics, lipidomics and clinical data using machine learning methods (2016), Acharjee et al., BMC Bioinformatics (2016), 17(Suppl 15):440

Bhattacharjee B, Shafi M, Acharjee A, Investigating the Influence Relationship Models for Stocks in Indian Equity Market: A Weighted Network Modelling Study. PLoS One. 2016, 15;11(11). doi: 10.1371/journal.pone.0166087.

Integration of multi-omics data for prediction of phenotypic traits using random forest (2016), Acharjee et al., BMC Bioinformatics, 17(Suppl 5):180

Extensible and Executable Stochastic Models of Fatty Acid and Lipid Metabolism, Computational Methods in Systems Biology (2014), Zardilis  et al., Lecture Notes in Computer Science, 8859:244-247

Comparison of regularized regression methods for ~omics data (2013), Acharjee et al., Journal of Metabolomics, 3:126

Untargeted metabolic quantitative trait loci analyses reveal a relationship between primary metabolism and potato tuber quality (2012), Carreno-Quintero et al., Plant Physiology, 158:1306-18  

Data integration and network reconstruction with ~omics data using Random Forest regression in potato (2011), Acharjee et al., Analytica Chimica Acta, 705:56–63