Dietrich Rebholz-Schuhmann
Dietrich Rebholz-Schuhmann
ZB MED -- Information Center for Life Sciences
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Text processing through Web services: calling Whatizit
D Rebholz-Schuhmann, M Arregui, S Gaudan, H Kirsch, A Jimeno
Bioinformatics 24 (2), 296-298, 2008
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
Text-mining solutions for biomedical research: enabling integrative biology
D Rebholz-Schuhmann, A Oellrich, R Hoehndorf
Nature Reviews Genetics 13 (12), 829-839, 2012
Facts from text—is text mining ready to deliver?
D Rebholz-Schuhmann, H Kirsch, F Couto
PLoS biology 3 (2), e65, 2005
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
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
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
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
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 (2), 1-15, 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, ...
The Journal of Immunology 145 (7), 2132-2139, 1990
Resolving abbreviations to their senses in Medline
S Gaudan, H Kirsch, D Rebholz-Schuhmann
Bioinformatics 21 (18), 3658-3664, 2005
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
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
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
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
Ontology refinement for improved information retrieval
A Jimeno-Yepes, R Berlanga-Llavori, D Rebholz-Schuhmann
Information Processing & Management 46 (4), 426-435, 2010
GOAnnotator: linking protein GO annotations to evidence text
FM Couto, MJ Silva, V Lee, E Dimmer, E Camon, R Apweiler, H Kirsch, ...
Journal of biomedical discovery and collaboration 1 (1), 1-6, 2006
Gene Regulation Ontology (GRO): design principles and use cases
E Beisswanger, V Lee, JJ Kim, D Rebholz-Schuhmann, A Splendiani, ...
MIE, 9-14, 2008
MedEvi: retrieving textual evidence of relations between biomedical concepts from Medline
J Kim, P Pezik, D Rebholz-Schuhmann
Bioinformatics 24 (11), 1410-1412, 2008
Integrating protein-protein interactions and text mining for protein function prediction
S Jaeger, S Gaudan, U Leser, D Rebholz-Schuhmann
BMC bioinformatics 9 (8), 1-10, 2008
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