Daniel Hanisch

982 total citations
10 papers, 668 citations indexed

About

Daniel Hanisch is a scholar working on Molecular Biology, Artificial Intelligence and Oncology. According to data from OpenAlex, Daniel Hanisch has authored 10 papers receiving a total of 668 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 2 papers in Artificial Intelligence and 1 paper in Oncology. Recurrent topics in Daniel Hanisch's work include Bioinformatics and Genomic Networks (6 papers), Biomedical Text Mining and Ontologies (5 papers) and Gene Regulatory Network Analysis (3 papers). Daniel Hanisch is often cited by papers focused on Bioinformatics and Genomic Networks (6 papers), Biomedical Text Mining and Ontologies (5 papers) and Gene Regulatory Network Analysis (3 papers). Daniel Hanisch collaborates with scholars based in Germany and South Korea. Daniel Hanisch's co-authors include Ralf Zimmer, Juliane Fluck, Heinz‐Theodor Mevissen, Alexander Zien, Thomas Lengauer, Katrin Fundel, Florian Sohler, Thomas Aigner, Dong‐Yup Lee and Sang Yup Lee and has published in prestigious journals such as Bioinformatics, Journal of Bone and Joint Surgery and BMC Bioinformatics.

In The Last Decade

Daniel Hanisch

10 papers receiving 628 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Daniel Hanisch Germany	8	545	248	79	49	27	10	668
Isabel Rojas Germany	15	558 1.0×	192 0.8×	63 0.8×	14 0.3×	33 1.2×	36	814
Ioannis Iliopoulos Greece	14	399 0.7×	83 0.3×	63 0.8×	5 0.1×	24 0.9×	27	627
Tor-Kristian Jenssen Norway	6	428 0.8×	128 0.5×	39 0.5×	7 0.1×	10 0.4×	9	495
Zun Liu China	10	142 0.3×	39 0.2×	127 1.6×	18 0.4×	10 0.4×	28	405
Carlos Cano Spain	12	359 0.7×	82 0.3×	171 2.2×	3 0.1×	28 1.0×	36	547
William A. Baumgartner United States	18	1.1k 2.0×	867 3.5×	66 0.8×	9 0.2×	63 2.3×	33	1.3k
Sylvain Soliman France	13	421 0.8×	82 0.3×	127 1.6×	13 0.3×	10 0.4×	44	589
Ka‐Lok Ng Taiwan	13	356 0.7×	73 0.3×	139 1.8×	6 0.1×	12 0.4×	59	510
Susanne M. Humphrey United States	14	638 1.2×	512 2.1×	50 0.6×	5 0.1×	94 3.5×	35	844
Mohamed Elati France	11	197 0.4×	42 0.2×	20 0.3×	15 0.3×	8 0.3×	35	320

Countries citing papers authored by Daniel Hanisch

Since Specialization

Citations

This map shows the geographic impact of Daniel Hanisch's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniel Hanisch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Hanisch more than expected).

Fields of papers citing papers by Daniel Hanisch

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Hanisch. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel Hanisch. The network helps show where Daniel Hanisch may publish in the future.

Co-authorship network of co-authors of Daniel Hanisch

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Hanisch. A scholar is included among the top collaborators of Daniel Hanisch based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniel Hanisch. Daniel Hanisch is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

Hanisch, Daniel, Katrin Fundel, Heinz‐Theodor Mevissen, Ralf Zimmer, & Juliane Fluck. (2005). ProMiner: rule-based protein and gene entity recognition. BMC Bioinformatics. 6(S1). S14–S14. 229 indexed citations

Hanisch, Daniel, Florian Sohler, & Ralf Zimmer. (2004). ToPNet—an application for interactive analysis of expression data and biological networks. Bioinformatics. 20(9). 1470–1471. 16 indexed citations

Lee, Dong‐Yup, et al.. (2004). Knowledge representation model for systems-level analysis of signal transduction networks.. PubMed. 15(2). 234–43. 11 indexed citations

Hanisch, Daniel, Katrin Fundel, Heinz‐Theodor Mevissen, Ralf Zimmer, & Juliane Fluck. (2004). ProMiner: Organism-specific protein name detection using approximate string matching. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 16 indexed citations

Sohler, Florian, Daniel Hanisch, & Ralf Zimmer. (2004). New methods for joint analysis of biological networks and expression data. Bioinformatics. 20(10). 1517–1521. 55 indexed citations

Gieger, Christian, Daniel Hanisch, Juliane Fluck, et al.. (2004). S26.2: Using Text Mining Networks for the Context Specific Interpretation of Gene Expression Data. Biometrical Journal. 46(S1). 56–56. 2 indexed citations

Aigner, Thomas, Alexander Zien, Daniel Hanisch, & Ralf Zimmer. (2003). GENE EXPRESSION IN CHONDROCYTES ASSESSED WITH USE OF MICROARRAYS. Journal of Bone and Joint Surgery. 85. 117–123. 53 indexed citations

Hanisch, Daniel, Alexander Zien, Ralf Zimmer, & Thomas Lengauer. (2002). Co-clustering of biological networks and gene expression data. Bioinformatics. 18(suppl_1). S145–S154. 200 indexed citations

Freudenberg, Jan, Ralf Zimmer, Daniel Hanisch, & Thomas Lengauer. (2002). A hypergraph-based method for unification of existing protein structure- and sequence-families.. PubMed. 2(3). 339–49. 3 indexed citations

10.

Hanisch, Daniel, Juliane Fluck, Heinz‐Theodor Mevissen, & Ralf Zimmer. (2002). PLAYING BIOLOGY'S NAME GAME: IDENTIFYING PROTEIN NAMES IN SCIENTIFIC TEXT. PubMed. 403–414. 83 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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