CelliVerse
An integrated R framework for data-driven single-cell clustering, marker discovery, marker assessment and cell type annotation.
Computational methods for cancer and single-cell biology
BIOINFORMATICS · SYSTEMS BIOLOGY · AI FOR BIOMEDICINE
I am Adrian Salavaty, a bioinformatician and systems biologist developing computational methods and open-source tools for single-cell, spatial and multi-omics cancer research.
Single-cell & spatial omics
Cancer multi-omics
Open-source method development
Explore research software View publications
Senior Bioinformatician & Senior Cancer Scientist · Peter MacCallum Cancer Centre · Melbourne
About
PROFILE
Turning high-dimensional biological data into interpretable methods and tools.
I work at the intersection of bioinformatics, systems biology, cancer genomics and computational method development. My research focuses on extracting robust biological structure from complex omics data, particularly single-cell, spatial and multi-omics datasets.
At Peter MacCallum Cancer Centre, I work across translational cancer research and bioinformatics. I also develop open-source computational frameworks, including CelliVerse, ClustoCell, ExIR and influential, with an emphasis on methods that are interpretable, reusable and practical for researchers.
Research Focus
Computational approaches designed around biological questions, not software conventions.
Single-cell & Spatial Omics
Cell-state discovery, clustering, marker identification, annotation, spatial organisation and translational analysis.
Cancer Multi-omics
Integrated analysis of transcriptomic, proteomic and genomic data to resolve tumour biology and clinically relevant signals.
Systems & Network Biology
Graph-based modelling, network reconstruction, feature prioritisation and interpretable biological systems analysis.
AI-assisted Bioinformatics
Practical AI and agent workflows that make advanced analysis tools easier to use without obscuring the underlying evidence.
Research Software & Methods
Open-source computational tools, algorithms and interactive resources.
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ClustoCell
A reference-independent framework for resolving cell types and states from single-cell transcriptomes using cell-intrinsic expression organisation.
Influential Python package
Identification and Classification of the Most Influential Nodes.
Influential R package
Identification and Classification of the Most Influential Nodes.
AutoClone Shiny App
AutoClone Shiny App; automatic analysis of genetic labelling data and clonality assessment.
Centrality-based Network Visualization
Centrality-based Network Visualization.
Computational Cell Manipulation
Evaluation of the impact of knockout or over-expression of a node (e.g. gene, protein, etc.) within a network.
ExIR
ExIR; a versatile one-stop model for the extraction, classification, and prioritization of candidate genes from experimental data.
ExIR Shiny App
ExIR Shiny App; a user-friendly web app for running the ExIR model on high-throughput data.
ExIR Visualization
Visualization of ExIR results.
Influential Shiny App
Influential Shiny App; a landing and information page for introducing the influential software package.
IVI
Integrated Value of Influence; An Integrative Method for the Identification of the Most Influential Nodes within Networks.
IVI Shiny App
IVI Shiny App; a user-friendly web app for calculating the influence of network nodes using the IVI algorithm.
Selected Publications & Preprints
Recent work across computational biology, single-cell analysis and systems biology.
Experience
Selected research and computational biology roles.
Senior Bioinformatician
- Single-cell, spatial and bulk omics analysis
- Multi-omics integration and computational method development
- Systems biology and translational cancer research
Senior Bioinformatics Scientist
- Omics and drug-screening analysis
- Systems biology and machine learning
- Computational pipeline development
Scientific Advisor
Scientific advisory work in bioinformatics and data analysis.
Research Officer (Bioinformatician and Systems Biologist)
- Omics data analysis
- Graph-based method development
- Cancer risk, driver and biomarker discovery
Scientific Advisor
Scientific advisory work at the interface of biomedical data and AI.
Tutor (TA)
Teaching across bioinformatics, genomics and medical biotechnology units.
Recognition & Funding
2026
RESEARCH FUNDING
AstraZeneca Research Grant
Named investigator on Multi-omics investigation of mCRPC rapid autopsy samples.
2022
AWARD
Postgraduate Publication Award
Monash University recognition based on publication record and prospects.
2021
AWARD
Best Oral Talk, People’s Choice
COMBINE symposium.
2021
RESEARCH FUNDING
Monash Data Futures Institute Seed Grant
Named investigator on Finding the right targets: most influential nodes in complex networks.
What Collaborators Say
Selected excerpts from research supervisors and collaborators.
“Adrian has a particularly strong skill set in the development of interactive applications using RShiny and similar tools, often exceeding my expectations around what is possible.”
“He has single-handedly transformed my group’s approach to computational systems biology, written new algorithms and invented completely new systems approaches.”
“His outstanding analytical capabilities combined with innovative thinking places him in the top 1% of students.”
Excerpts shortened for the homepage. Full references can be provided when relevant.
Contact
For scientific collaboration, methods, software or speaking enquiries.
- Melbourne, VIC
- Book an appointment
- Connect on LinkedIn
- Explore my GitHub