Mahdi is a Senior Scientist in Bioinformatics, with a background in clinical medicine. He is working with Professor Paul Matthews at UK Dementia Research Institute (DRI), at Imperial College London.
Mahdi is a part of the Multi-’omics Atlas Project (MAP) aimed to establish the first comprehensive multi-'omics atlas characterising the molecular neuropathology of Alzheimer’s disease. For example, he works with a team of bioinformaticians who develop a unique pipeline that provides a fast, comprehensive, and reproducible analysis of single cell/nuclei RNA-seq data. He has a particular interest in scRNA-seq dataset integration, cell-cell interaction, and spatial transcriptomics.
Mahdi completed his medical doctorate (MD) at Mashhad University of Medical Sciences (Mashhad, Iran) and then joined the Academic Center for Education, Culture, and Research (Mashhad, Iran) as a faculty member. In 2009, he was granted the prestigious International Postgraduate Award from the University of New South Wales in Australia which funded his PhD studies. During his PhD at the Victor Chang Cardiac Research Institute (Sydney, Australia), he successfully fine-mapped QTL underlying cardiac atrial septal defects using a mouse model, and completed a transcriptomic analysis of the atrial septum. In 2014, Mahdi joined QIMR Berghofer Medical Research Institute (Brisbane, Australia) as a postdoctoral bioinformatician where he led pioneering projects on follow-up of breast cancer GWAS loci with a heavy focus on understanding how non-coding GWAS variants influence cancer risk and progression. Mahdi moved to the UK in October 2019 to start his new position as a senior scientist in bioinformatics at UK DRI at Imperial College London.
Beesley J*, Sivakumaran H*, Moradi Marjaneh M* (*co-first author), et al. “eQTL colocalization analyses identifies NTN4 as a candidate breast cancer risk gene”. American Journal of Human Genetics. 2020; 21:S0002-9297(20)30274-3. DOI: 10.1016/j.ajhg.2020.08.006
Moradi Marjaneh M, et al. "Non-coding RNAs underlie genetic predisposition to breast cancer". Genome Biology. 2020; 21(1):7. DOI: 10.1186/s13059-019-1876-z
Beesley J*, Sivakumaran H*, Moradi Marjaneh M* (*co-first author), et al. "Chromatin interactome mapping at 139 independent breast cancer risk signals". Genome Biology. 2020; 21(1):8. DOI: 10.1186/s13059-019-1877-y
Fachal L, et al. "Fine-mapping of 150 breast cancer risk regions identifies 178 high confidence target genes". Nature Genetics. 2020; 52(1):56-73. DOI: 10.1038/s41588-019-0537-1
Betts JA*, Moradi Marjaneh M*, Al-Ejeh F* (*co-first author), et al. “Long Noncoding RNAs CUPID1 and CUPID2 Mediate Breast Cancer Risk at 11q13 by Modulating the Response to DNA Damage”. American Journal of Human Genetics. 2017; 101(2):255-66. DOI: 10.1016/j.ajhg.2017.07.007
Dunning AM, et al. “Breast cancer risk variants at 6q25 display different phenotype associations and regulate ESR1, RMND1 and CCDC170”. Nature Genetics. 2016; 48(4):374-86. DOI: 10.1038/ng.3521
Ghoussaini M, et al. “Evidence that the 5p12 variant rs10941679 confers susceptibility to estrogen receptor positive breast cancer through FGF10 and MRPS30 regulation”. American Journal of Human Genetics. 2016; 99(4):903-11. DOI: 10.1016/j.ajhg.2016.07.017
et al., 2020, Chromatin interactome mapping at 139 independent breast cancer risk signals, Genome Biology, Vol:21
et al., 2020, Non-coding RNAs underlie genetic predisposition to breast cancer, Genome Biology, Vol:21
et al., 2020, The clinical impact of quantitative cell-free DNA, KRAS, and BRAF mutations on response to anti-EGFR treatment in patients with metastatic colorectal cancer, Current Pharmaceutical Design, Vol:26, ISSN:1381-6128
et al., 2020, eQTL Colocalization Analyses Identify NTN4 as a Candidate Breast Cancer Risk Gene, American Journal of Human Genetics, Vol:107, ISSN:0002-9297, Pages:778-787
et al., 2020, Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes, Nature Genetics, Vol:52, ISSN:1061-4036