
Biography
Anthony Etuk (Toni) joined the Earlham Institute in February 2015 as a Research Software Engineer on the Collaborative Open Plant Omics' (COPO) project, a platform for plant scientists to describe, deposit and retrieve data more easily.
Toni completed his PhD in Computer Science at the University of Aberdeen. His area of interest was multi-agent systems, with a focus on computational models of trust and reputation. In particular, he investigated how these techniques could be inexpensively applied to support decision-making in distributed environments, such as crowdsourcing, peer-to-peer networks, pervasive computing, and sensor networks. He continues to explore these techniques, and a number of techniques from Machine Learning and statistics, in contexts of Open Science and Bioinformatics.
Toni has industry experience, working as a Programmer, Web/Database developer, and Customer Relationship Management (CRM) analyst/developer. In academia, he has worked as a Graduate/Teaching assistant.
Publications
Related reading.

Five Earlham Institute technologies you should be using

Differences make a difference: from one cell to a world of individuality

Sky’s the limit for new air sequencing technology

Focus on the future at EI Innovate

LITE–ing the way to game-changing technology

The art of being single: advanced single-cell sequencing technology

Why cloud computing is important for data-driven bioscience research

Generating a high-quality tilapia genome assembly: from sample to sequence

Earlham Institute unveils new Vizgen platform for spatial transcriptomics

Earlham Institute first UK site to receive Illumina NovaSeq X Plus

Machine learning tech that hunts for plant biomarkers awarded UKRI funding

New method and model address blindspot towards uncommon species in mixed samples

New HiFi platform increases sequencing power to help decode the genome of all life on earth

Building capacity in DNA sequencing for agricultural biosciences in Africa

Eagle Genomics and the Earlham Institute to deliver new microbiome multi-omics datasets and tools

When one become two: separating DNA for more accurate nanopore analysis
