Research & Academic Profile

Maria
Kalyva

Researcher and computional biologist with experience in cancer genomics, transcriptomics and bioinformatics. Passionate about interdisciplinary work and innovation.

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Computational biologist with deep expertise in cancer genomics and long-read multi-omics. My current research centres on characterising transcriptional diversity in lung cancer using long-read multiomic methods.

Experienced in integrating heterogeneous data modalities—including scRNA-seq, long-read RNA-seq, bulk transcriptomics, and whole-genome sequencing.

Location

London, United Kingdom

Expertise

Single-cell · Multi-omics · Cancer Genomics

Apr 2024 — Present

Postdoctoral Research Fellow

University College London (UCL) · Cancer Research UK Lung Cancer Centre of Excellence

Leading computational study on transcriptional diversity and isoform discovery using Oxford Nanopore long-read RNA sequencing. Developing bioinformatic pipelines for isoform quantification and differential transcript usage analysis. Supervising PhD students and contributing to grant applications.

Long-read RNA-seq Isoform Analysis Bioinformatics Multi-omics

Oct 2019 — Jan 2024

PhD Researcher

University of Cambridge & EMBL-EBI

Reconstructed cellular lineage histories and quantified clonal dynamics at single-cell resolution using phylogenetic inference and Bayesian phylodynamic modelling. Developed cell-type deconvolution approaches using single-cell RNA-seq reference atlases. Integrated multi-modal datasets to study clonal architecture and genomic-state relationships. Thesis: "Elucidating the evolutionary dynamics of MSI tumours at the single-cell level"

Phylogenetics Single-cell RNA-seq Clonal Analysis Multi-modal Integration

Jan 2019 — Jul 2019

Research Assistant (Bioinformatics)

University College London (UCL)

Identified somatic copy number alterations and structural variants from whole-genome sequencing of human brain tissue. Implemented and optimised variant-calling pipelines for large-scale WGS datasets with custom filtering scripts for somatic variant detection.

Variant Calling WGS Analysis Pipeline Development

Programming

  • R, Python, Bash
  • Nextflow, Git
  • Singularity/Apptainer
  • HPC & Cloud Computing

Omics & Genomics

  • scRNA-seq & Long-read RNA/DNA
  • Isoform Quantification
  • Variant Calling (SNVs, CNVs, SVs)
  • Clonal Deconvolution

Computational Biology

  • Phylogenetic Reconstruction
  • Cell-type Deconvolution
  • Multi-omic Integration
  • Differential Analysis

Sep 2019 — Jan 2024

PhD in Cancer Genomics and Evolution

University of Cambridge & EMBL-EBI

Thesis: "Elucidating the evolutionary dynamics of MSI tumours at the single-cell level". College Senior Scholarship recipient (2020–2023).

2014 — 2018

BSc in Molecular Biology (Top 10%)

University of Crete

Erasmus traineeship at University College London. World Hellenic Biomedical Association Scholarship (2018).

Kalyva M, McGranahan N. (2026).

Redefining cancer drivers with tissue-specific context.

Cancer Cell (in press)

Kalyva M, Kildisiute G, Elmentaite R, et al. (2024).

Transcriptional signals of transformation in human cancer.

Genome Medicine

Van Egeren D, Kamaz B, Liu S, Kalyva M, et al. (2022).

Transcriptional differences between JAK2-V617F and wild-type bone marrow cells in myeloproliferative neoplasms.

Experimental Hematology

Van Egeren D, Escabi J, Nguyen M, Kalyva M, et al. (2021).

Reconstructing lineage histories and differentiation trajectories of individual cancer cells in myeloproliferative neoplasms.

Cell Stem Cell

Sekar S, Tomasini L, Proukakis C, Kalyva M, et al. (2020).

Complex mosaic structural variations in human fetal brains.

Genome Research

Perez-Rodriguez D, Kalyva M*, et al. (*equal contribution) (2019).

Investigation of somatic CNVs in brains of synucleinopathy cases using targeted SNCA analysis and single cell sequencing.

Acta Neuropathologica Communications

College Senior Scholarship

Fitzwilliam College, University of Cambridge (2020–2023)

World Hellenic Biomedical Association Scholarship

2018

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