• An accessible proteogenomics informatics resource for cancer researchers 

      Chambers, Matthew C.; Jagtap, Pratik D.; Johnson, James E.; McGowan, Thomas; Kumar, Praveen; Onsongo, Getiria; Guerrero, Candace R.; Barsnes, Harald; Vaudel, Marc; Martens, Lennart; Grüning, Björn; Cooke, Ira R.; Heydarian, Mohammad; Reddy, Karen L.; Griffin, Timothy J. (Peer reviewed; Journal article, 2017)
      Proteogenomics has emerged as a valuable approach in cancer research, which integrates genomic and transcriptomic data with mass spectrometry–based proteomics data to directly identify expressed, variant protein sequences ...
    • Perspectives on automated composition of workflows in the life sciences [version 1; peer review: 2 approved] 

      Lamprecht, Anna-Lena; Palmblad, Magnus; Ison, Jon; Schwämmle, Veit; Al Manir, Mohammad Sadnan; Altintas, Ilkay; Baker, Christopher J. O.; Ben Hadj Amor, Ammar; Capella-Gutierrez, Salvador; Charonyktakis, Paulos; Crusoe, Michael R.; Gil, Yolanda; Goble, Carole; Griffin, Timothy J.; Groth, Paul; Ienasescu, Hans; Jagtap, Pratik; Kalaš, Matúš; Kasalica, Vedran; Khanteymoori, Alireza; Kuhn, Tobias; Mei, Hailiang; Ménager, Hervé; Möller, Steffen; Richardson, Robin A.; Robert, Vincent; Soiland-Reyes, Stian; Stevens, Robert; Szaniszlo, Szoke; Verberne, Suzan; Verhoeven, Aswin; Wolstencroft, Katherine (Journal article; Peer reviewed, 2021)
      Scientific data analyses often combine several computational tools in automated pipelines, or workflows. Thousands of such workflows have been used in the life sciences, though their composition has remained a cumbersome ...