Text processing through Web services: calling Whatizit D Rebholz-Schuhmann, M Arregui, S Gaudan, H Kirsch, A Jimeno Bioinformatics 24 (2), 296-298, 2008 | 293 | 2008 |
Text-mining solutions for biomedical research: enabling integrative biology D Rebholz-Schuhmann, A Oellrich, R Hoehndorf Nature Reviews Genetics 13 (12), 829-839, 2012 | 273 | 2012 |
EBIMed—text crunching to gather facts for proteins from Medline D Rebholz-Schuhmann, H Kirsch, M Arregui, S Gaudan, M Riethoven, ... Bioinformatics 23 (2), e237-e244, 2007 | 266 | 2007 |
Deep learning-based clustering approaches for bioinformatics MR Karim, O Beyan, A Zappa, IG Costa, D Rebholz-Schuhmann, ... Briefings in bioinformatics 22 (1), 393-415, 2021 | 240 | 2021 |
Automatic recognition of conceptualization zones in scientific articles and two life science applications M Liakata, S Saha, S Dobnik, C Batchelor, D Rebholz-Schuhmann Bioinformatics 28 (7), 991-1000, 2012 | 217 | 2012 |
MeSH Up: effective MeSH text classification for improved document retrieval D Trieschnigg, P Pezik, V Lee, F De Jong, W Kraaij, ... Bioinformatics 25 (11), 1412-1418, 2009 | 195 | 2009 |
Facts from text—is text mining ready to deliver? D Rebholz-Schuhmann, H Kirsch, F Couto PLoS biology 3 (2), e65, 2005 | 188 | 2005 |
Assessment of disease named entity recognition on a corpus of annotated sentences A Jimeno, E Jimenez-Ruiz, V Lee, S Gaudan, R Berlanga, ... BMC bioinformatics 9 (Suppl 3), S3, 2008 | 151 | 2008 |
Adverse immune reactions to gold. I. Chronic treatment with an Au (I) drug sensitizes mouse T cells not to Au (I), but to Au (III) and induces autoantibody formation. D Schuhmann, M Kubicka-Muranyi, J Mirtschewa, J Günther, P Kind, ... Journal of immunology (Baltimore, Md.: 1950) 145 (7), 2132-2139, 1990 | 143 | 1990 |
Resolving abbreviations to their senses in Medline S Gaudan, H Kirsch, D Rebholz-Schuhmann Bioinformatics 21 (18), 3658-3664, 2005 | 134 | 2005 |
CALBC silver standard corpus D Rebholz-Schuhmann, AJJ Yepes, EM Van Mulligen, N Kang, J Kors, ... Journal of bioinformatics and computational biology 8 (01), 163-179, 2010 | 132 | 2010 |
Text mining for biology-the way forward: opinions from leading scientists RB Altman, CM Bergman, J Blake, C Blaschke, A Cohen, F Gannon, ... Genome biology 9, 1-15, 2008 | 130 | 2008 |
Using argumentation to extract key sentences from biomedical abstracts P Ruch, C Boyer, C Chichester, I Tbahriti, A Geissbühler, P Fabry, ... International journal of medical informatics 76 (2-3), 195-200, 2007 | 125 | 2007 |
Deepcovidexplainer: Explainable covid-19 predictions based on chest x-ray images M Karim, T Döhmen, D Rebholz-Schuhmann, S Decker, M Cochez, ... arXiv preprint arXiv:2004.04582 28, 2020 | 111 | 2020 |
Course tracking and contour extraction of retinal vessels from color fundus photographs: Most efficient use of steerable filters for model-based image analysis B Kochner, D Schuhmann, M Michaelis, G Mann, KH Englmeier Medical Imaging 1998: Image Processing 3338, 755-761, 1998 | 108 | 1998 |
Biological network extraction from scientific literature: state of the art and challenges C Li, M Liakata, D Rebholz-Schuhmann Briefings in bioinformatics 15 (5), 856-877, 2014 | 107 | 2014 |
Automatic extraction of mutations from Medline and cross‐validation with OMIM D Rebholz‐Schuhmann, S Marcel, S Albert, R Tolle, G Casari, H Kirsch Nucleic Acids Research 32 (1), 135-142, 2004 | 94 | 2004 |
Ontology refinement for improved information retrieval A Jimeno-Yepes, R Berlanga-Llavori, D Rebholz-Schuhmann Information Processing & Management 46 (4), 426-435, 2010 | 89 | 2010 |
A multilingual gold-standard corpus for biomedical concept recognition: the Mantra GSC JA Kors, S Clematide, SA Akhondi, EM Van Mulligen, ... Journal of the American Medical Informatics Association 22 (5), 948-956, 2015 | 85 | 2015 |
Gene Regulation Ontology (GRO): design principles and use cases E Beisswanger, V Lee, JJ Kim, D Rebholz-Schuhmann, A Splendiani, ... MIE, 9-14, 2008 | 84 | 2008 |