Dr Animesh Acharjee PhD

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

Contact details

Email: a.acharjee@bham.ac.uk

View my research portal

Address: Institute for Cancer and Genomic Sciences
Haworth Building
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 Institute 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 70 papers and his h index is 22 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, Zlobec I, Aeschbacher P, Perren A, Gloor B. Spatially restricted tumour-associated and host-associated immune drivers correlate with the recurrence sites of pancreatic cancer. Gut. 2023 Aug;72(8):1523-1533. doi: 10.1136/gutjnl-2022-329371. Epub 2023 Feb 15. PMID: 36792355.

Acharjee A#, Agarwal P, Gkoutos GV. Editorial: Integrative multi-modal, multi-omics analytics for the better understanding of metabolic diseases. Front Endocrinol (Lausanne). 2023 Sep 8;14:1266557. doi: 10.3389/fendo.2023.1266557. PMID: 37745706; PMCID: PMC10516571.

Kaushal A, Mandal A, Khanna D, Acharjee A. Analysis of the opinions of individuals on the COVID-19 vaccination on social media. Digit Health. 2023 Jul 10;9:20552076231186246. doi: 10.1177/20552076231186246. PMID: 37448782; PMCID: PMC10336764.

Acharjee A#. Explainable AI for gut microbiome-based diagnostics: colorectal cancer as a case study. Diagnosis (Berl). 2023 Jun 19;10(4):448-449. doi: 10.1515/dx-2023-0062. PMID: 37328267.

Irvine HJ, Acharjee A, Wolcott Z, Ament Z, Hinson HE, Molyneaux BJ, Simard JM, Sheth KN, Kimberly WT. Hypoxanthine is a pharmacodynamic marker of ischemic brain edema modified by glibenclamide. Cell Rep Med. 2022 Jun 9:100654. doi: 10.1016/j.xcrm.2022.100654. PMID: 35700741.

Wood H*, Acharjee A*, Pearce H, Quraishi MN, Powell R, Rossiter A, Beggs A, Ewer A, Moss P, Toldi G. Breastfeeding promotes early neonatal regulatory T-cell expansion and immune tolerance of non-inherited maternal antigens. Allergy. 2021. doi: 10.1111/all.14736.

Sanders FWB, Acharjee A*, Walker C*, Marney L, Roberts LD, Imamura F, Jenkins B, Case J, Ray S, Virtue S, Vidal-Puig A, Kuh D, Hardy R, Allison M, Forouhi N, Murray AJ, Wareham N, Vacca M, Koulman A, Griffin JL. Hepatic steatosis risk is partly driven by increased de novo lipogenesis following carbohydrate consumption. Genome Biol. 2018 ;19(1):79. doi: 10.1186/s13059-018-1439-8.

Quraishi MN*, Acharjee A*, Beggs AD, Horniblow R, Tselepis C, Gkoutos G, Ghosh S, Rossiter AE, Loman N, van Schaik W, Withers D, Walters JRF, Hirschfield GM, Iqbal TH. A Pilot Integrative Analysis of Colonic Gene Expression, Gut Microbiota, and Immune Infiltration in Primary Sclerosing Cholangitis-Inflammatory Bowel Disease: Association of Disease With Bile Acid Pathways. J Crohns Colitis. 2020 ;14(7):935-947. doi: 10.1093/ecco-jcc/jjaa021. PMID: 32016358; PMCID: PMC7392170.

Xu Y, Nash K, Acharjee A, Gkoutos GV. CACONET: a novel classification framework for microbial correlation networks. Bioinformatics. 2022 Jan 4:btab879. doi: 10.1093/bioinformatics/btab879. PMID: 34983063.

Acharjee A#, Kloosterman B, de Vos RC, Werij JS, Bachem CW, Visser RG, Maliepaard C. Data integration and network reconstruction with -omics data using Random Forest regression in potato. Anal Chim Acta. 2011, 31;705(1-2):56-63

Bravo-Merodio L*, Acharjee A*,#, Hazeldine J, Bentley C, Foster M, Gkoutos GV#, Lord JM. Machine learning for the detection of early immunological markers as predictors of multi-organ dysfunction. Sci Data. 2019 ;6(1):328. doi: 10.1038/s41597-019-0337-6.

Acharjee A, Prentice P, Acerini C, Smith J, Ong K, Griffin JL, Dunger D, Koulman A, The translation of lipid profiles to nutritional biomarkers in the study of infant metabolism. Metabolomics. 2017, 13(3):25.

Acharjee A, Ament Z, West JA, Stanley E, Griffin JL, Integration of metabolomics, lipidomics and clinical data using a machine learning method. 2016, BMC Bioinformatics. 2016, 17(Suppl 15):440

Acharjee A, Kloosterman B, Visser RG, Maliepaard C. Integration of multi-omics data for prediction of phenotypic traits using random forest. BMC Bioinformatics. 2016, 6;17 (Suppl 5):180

For other papers, please refer to GoogleScholar.

View all publications in research portal