CompLifeSci Guest seminar: Using text mining in biomedical databases
Prof. Lars Juhl Jensen, Disease Systems Biology Program, University of Copenhagen: Using text mining in biomedical databases
Coffee at 10:45
Lars Juhl Jensen started his research career in Søren Brunak’s group at the Technical University of Denmark (DTU), from which he in 2002 received the Ph.D. degree in bioinformatics for his work on non-homology based protein function prediction. During this time, he also developed methods for visualization of microbial genomes, pattern recognition in promoter regions, and microarray analysis. From 2003 to 2008, he was at the European Molecular Biology Laboratory (EMBL) where he worked on literature mining, integration of large-scale experimental datasets, and analysis of biological interaction networks. Since the beginning of 2009, he has continued this line of research as a professor at the Novo Nordisk Foundation Center for Protein Research at the Panum Institute in Copenhagen and as a co-founder and scientific advisor of Intomics A/S.
Selected publications:
Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, Simonovic M, Doncheva NT, Morris JH, Bork P*, Jensen LJ* and von Mering C* (2019). STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Research, 47:D607-D613.
Oprea TI, Bologa CG, Brunak S, Campbell A, Gan GN, Gaulton A, Gomez SM, Guha R, Hersey A, Holmes J, Jadhav A, Jensen LJ, Johnson GL, Karlson A, Leach AR, Ma’ayan A, Malovannaya A, Mani S, Mathias SL, McManus MT, Meehan TF, von Mering C, Muthas D, Nguyen DT, Overington JP, Papadatos G, Qin J, Reich C, Roth BL, Schürer SC, Simeonov A, Sklar LA, Southall N, Tomita S, Tudose I, Ursu O, Vidovic D, Waller A, Westergaard D, Yang JJ and Zahoránszky-Köhalmi G (2018). Unexplored therapeutic opportunities in the human genome. Nature Reviews Drug Discovery, 17:377.
Westergaard D, Stærfeldt H-H, Tønsberg C, Jensen LJ* and Brunak S* (2018). Text mining of 15 million full-text scientific articles. PLOS Computational Biology, 14:e1005962.
Pafilis E, Buttigieg PL, Ferrell B, Pereira E, Schnetzer J, Arvanitidis C and Jensen LJ (2016). EXTRACT: Interactive extraction of environment metadata and term suggestion for metagenomic sample annotation. Database, 2016:baw005.
Pletscher-Frankild S, Pallejà A, Tsafou K, Binder JX and Jensen LJ (2015). DISEASES: Text mining and data integration of disease–gene associations. Methods, 74:83-89