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It’s all about DNA… decoding


The AGRF Data Science team, which was previously led by Dr. Lesley Gray, included key members Dr. Rust Turakulov and Naga Kasinadhuni. Although the Data Science group has been disbanded, we remain interested in big data mining for genomics questions, translating numerical complexities into compelling biological narratives. We are passionate about uncovering insights encoded within genomes and navigating the data landscape with precision and innovation. Our focus is on bringing clarity to the biological stories hidden within the numerical vastness of genetic information.


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Find My SNP

Find my SNP

CRC TiME :: DATA BROWSER

CRC TiME UMAP application

Microbial Landscape :: DivPro + AMI

CRC TiME UMAP application

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TSO500 QC metrics

 TSO500 multi runs QC

Exome QC metrics

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Expertise

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Our team offers expertise in bioinformatics analysis and manages large-scale data integration and workflows, specializing in microbiome and genomic sequencing datasets, population studies, and genome assemblies. We develop intuitive visualization dashboards and provide robust data hosting solutions to facilitate exploration and understanding of complex biological data.

Lesley Gray, PhD

Data Science & Strategy Manager
Lesley Gray is a seasoned bioinformatics expert, holding a PhD and postdoctoral experience in quantitative genetics. As the Data Science & Strategy Manager at the Australian Genome Research Facility, she leverages her extensive technical background across a spectrum of genomic data types to deliver insights from genomic data and define AGRF’s Data Strategy. Her expertise spans agricultural, bacterial, and clinical genomic applications. In her service laboratory role, she has delivered insights from a wide array of sequencing technologies and genomic research areas. Lesley is passionate about integrating strategy and data science with bioinformatics to craft effective, applied solutions.

Naga Kasinashuni

Data Scientist
Naga Kasinashuni is an expert bioinformatician with extensive experience in a service laboratory setting. His expertise includes defining bespoke bioinformatics analyses for complex genomic data, pipeline development, and managing genomic data through advanced databasing and dashboarding techniques. Naga excels in data science and is adept at navigating the challenges posed by the inherently variable quality of data from emerging technologies. He has developed numerous data management tools, databases, and visualizations. With a passion for unpacking genomic data, Naga specializes in the intricate analysis of complex metagenomic datasets.

Rust Turakulov, PhD

Senior Developer
Rust Turakulov’s professional journey has been rich in bioinformatics, data analysis, and pipeline development, showcasing a progressive mastery of Perl, Shell, SQL, R, and long list of bioinformatics tools. His work has included clustering algorithms for genetic classification, developing GATK and other callers genotyping pipelines, integrating complex data-flow systems. Rust has also created automated workflows and reporting for the bacterial 16S sequence analysis and contributed to patented diagnostic methods. His expertise extends to developing analytical methods for very large genomics data, tumor classification based on multiomics data, and creating comprehensive data management portals. Recently, he has focused on integration of large datasets from public and private domains and the development of interactive user interfaces, showcasing his deep proficiency in bioinformatics and data-driven research.

Past

AGTA 2024

Australian Genome Transfer Association 2024 Conference poster

Critically Assessing the Influence of Variable Region Selection on Bacterial Community Profiling: 16S rDNA and the sequencing. Open PDF poster


Genivate23

Melbourne Genomics co funded two projects with AGRF to establish MVP for data tracking platforms. The scope for those project described in below documents:

  • Federated Clinical Data Registry Platform: Open PDF document.
  • Clinical Data Lineage (AGRF data ledger) platform: Open PDF document.


  • The hyperlink provided to the websites below may not work as AWS machine could be switched off.