Dr Animesh Acharjee PhD

Dr Animesh Acharjee

Institute of Cancer and Genomic Sciences
Assistant Professor
Deputy Programme Director, MSc in Health Data Science (Dubai)

Contact details

Address
Department of Cancer and Genomic Sciences
University of Birmingham
Edgbaston
Birmingham
B15 2TT

Animesh Acharjee is an Assistant Professor of Integrative Analytics and AI (Health Data Science) and Deputy Programme Director, MSc in Health Data Science (Dubai) in the Department of Cancer and Genomic Sciences. 

Qualifications

  • PhD in Omics data analysis, Wageningen University, The Netherlands
  • MSc in Bioinformatics, IBAB, Bangalore, India
  • BTech in Electrical Engineering, NERIST, India

Biography

Dr. Acharjee did his undergraduate degree in Electrical Engineering from North Eastern Regional Institute of Technology (NERIST), Itanagar, India and Masters in Bioinformatics from Institute of Bioinformatics and Applied Biotechnology, Bangalore , India. After his Masters, he earned his PhD from Wageningen University, The Netherlands, on applied machine learning and data analysis. After his PhD he moved to Lyon, France, for his post-doctoral study with Synergie Lyon Cancer Centre as a Biostatistician where he extensively worked on big data analytics, cloud computing. After his post-doctoral study he was offered a scientist position with BASF Cropdesign, Belgium.

Before joining University of Birmingham and Queen Elizabeth Hospital he was working with University of Cambridge, Cambridge, UK focusing on metabolic driven diseases like Obesity, T2-diabetis using high throughput metabolomics, lipidomics technologies. His research interests includes integrative data analytics, predictive biomarker discovery, bioinformatics methods for diagnostics and network biology. Throughout his career, he was offered many fellowships from British Council, Dutch Government and Newton fellowships. He has published many papers in the international journals and actively collaborate with many Universities, for example Harvard University and University of Cambridge. So far, he has published 83 papers, and his h index is 25 based on google scholar.

Teaching

Research

1. Integrative analytics

Dr. Acharjee applies novel approaches to the diverse multi omics data e.g. genetics, transcriptomics, proteomics, metabolomics, single cell transcriptomics to integrate them and identify novel therapeutic mechanisms and/or disease mechanisms. The data sets used in those studies are often public (ex: TCGA, GEO etc) or stakeholders’ experimental data. To perform an integration, Dr. Acharjee often uses machine learning/AI methods derived from multiple experiments across many diseases. Some of the examples of integration are here: microbiome and inflammatory markers in infant cohort (Wood and Acharjee et al., Allergy, 2021); microbiome, metabolome and single cell sequence data in the colon cancer cohort (Bisht et al.,  Int J Mol Sci. 2021; Quraishi and Acharjee et al., J Crohns Colitis, 2020) and multiple metabolomics data sets integration (Acharjee et al., BMC Bioinformatics, 2016).

2. Diagnostics

Unlike previous portfolio, this aspect considers single omics or clinical data including variety of machine learning methods. Some examples include identification of the markers from cytokine profiling data (Bravo-Merodio and Acharjee et al., Sci Data. 2019), diagnostic marker from miRNA  (Di Pietro et al, Br J Sports Med. 2021);  metabolomics biomarker identification (Ament et al., Transl Stroke Res., 2021; Acharjee et al., Metabolomics, 2018).

3. Data analytics methods and workflow development

Dr. Acharjee is also interested to develop new bioinformatics tools /workflows that can be useful for the clinician or biologist. Some of the examples are: Microbiome analysis workflow (Bisht and Acharjee et al., Comput Biol Med, 2021), statistical power calculations online tool (Acharjee et al., BMC Medical Genomics, 2020), automatic feature selection form high dimensional omics data sets (Bravo-Merodio et al.,  J Transl Med. 2019).

Publications

Legend: * Sharing first or second authorship;  # Corresponding authorship

Major Publications

Karamitopoulou E, Wenning AS, Acharjee A, Aeschbacher P, Marinoni I, Zlobec I, Gloor B, Perren A. Spatial heterogeneity of immune regulators drives dynamic changes of local immune responses, affecting disease outcomes in pancreatic cancer. Clin Cancer Res. 2024 Jul 15. doi: 10.1158/1078-0432.CCR-24-0368. Epub ahead of print. PMID: 39007872.

Acharjee A#, Okyere D, Nath D, Nagar S, Gkoutos GV. Network dynamics and therapeutic aspects of mRNA and protein markers with the recurrence sites of pancreatic cancer. Heliyon. 2024 May 17;10(10):e31437. doi: 10.1016/j.heliyon.2024.e31437. PMID: 38803850; PMCID: PMC11128524.

Onwuka S, Bravo-Merodio L, Gkoutos GV, Acharjee A#. Explainable AI-prioritized plasma and fecal metabolites in inflammatory bowel disease and their dietary associations. iScience. 2024 Jun 17;27(7):110298. doi: 10.1016/j.isci.2024.110298. PMID: 39040076; PMCID: PMC11261406.

Cusworth S, Gkoutos GV, Acharjee A#. A novel generative adversarial network modelling for the class imbalance problem in high dimensional omics data. BMC Med Inform Decis Mak. 2024 Mar 28;24(1):90. doi: 10.1186/s12911-024-02487-2. PMID: 38549123

Acharjee A#*, Wijesinghe SN*, Russ D, Gkoutos G, Jones SW. Cross-species transcriptomics identifies obesity associated genes between human and mouse studies. J Transl Med. 2024 Jun 25;22(1):592. doi: 10.1186/s12967-024-05414-1. PMID: 38918843; PMCID: PMC11197204.

Pal N*, Acharjee A*, Ament Z*, Dent T, Yavari A, Mahmod M, Ariga R, West J, Steeples V, Cassar M, Howell NJ, Lockstone H, Elliott K, Yavari P, Briggs W, Frenneaux M, Prendergast B, Dwight JS, Kharbanda R, Watkins H, Ashrafian H, Griffin JL. Metabolic profiling of aortic stenosis and hypertrophic cardiomyopathy identifies mechanistic contrasts in substrate utilization. FASEB J. 2024 Mar 31;38(6):e23505. doi: 10.1096/fj.202301710RR. PMID: 38507255.

Sadozai H*, Acharjee A*,#, Kayani HZ, Gruber T, Gorczynski RM, Burke B. High hypoxia status in pancreatic cancer is associated with multiple hallmarks of an immunosuppressive tumor microenvironment. Front Immunol. 2024 Mar 6;15:1360629. doi: 10.3389/fimmu.2024.1360629. PMID: 38510243; PMCID: PMC10951397.

Das A, Gkoutos GV, Acharjee A#. Analysis of translesion polymerases in colorectal cancer cells following cetuximab treatment: A network perspective. Cancer Med. 2024 Jan;13(1):e6945. doi: 10.1002/cam4.6945. PMID: 39102671; PMCID: PMC10809876.

For other papers, please refer to GoogleScholar.

View all publications in research portal