omics integration, reproducible research, mass spectrometry, proteomics, peptidomics, metabolomics, workflow, Galaxy, microservices, Kubernetes
Payam received his Ph.D. in medical bioinformatics from the Uppsala University in 2017 where he worked on various bioinformatics projects mainly focusing on mass spectrometry (MS)-based proteomics, peptidomics, and metabolomics. The projects ranged from simple label-free proteomics to more sophisticated labeled/unlabelled experiments. In 2015, Payam joined the PhenoMeNal consortium where he worked on a variety of metabolomics projects including cloud-based metabolite identification and quantification tools/workflows.
In 2018, Payam started his Postdoc at Karolinska Institute where he primarily worked on the MS-based identification of intact (neuro)peptides. This includes designing and evaluating computational tools/workflows to facilitate automatic de novo and database-based characterization of intact peptides.
Payam mainly supports start to end pre-processing and statistical analyzing of various MS experiment. He also supports designing computational workflows for analyzing such data. His current research interests are proteomics, peptidomics, metabolomics, tool/workflow development, data integration, cloud-based data analysis, microservices-based architecture, Kubernetes-based workflows, Galaxy workflows, and reproducible data analysis.