Daniel Daniš

3.5k total citations
29 papers, 363 citations indexed

About

Daniel Daniš is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Daniel Daniš has authored 29 papers receiving a total of 363 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 11 papers in Genetics and 6 papers in Cancer Research. Recurrent topics in Daniel Daniš's work include Genomics and Rare Diseases (10 papers), Biomedical Text Mining and Ontologies (6 papers) and Cancer Genomics and Diagnostics (5 papers). Daniel Daniš is often cited by papers focused on Genomics and Rare Diseases (10 papers), Biomedical Text Mining and Ontologies (6 papers) and Cancer Genomics and Diagnostics (5 papers). Daniel Daniš collaborates with scholars based in United States, Germany and United Kingdom. Daniel Daniš's co-authors include Peter N. Robinson, Julius O.B. Jacobsen, Damian Smedley, Leigh Carmody, Michael Gargano, Melissa Haendel, Julie A. McMurry, Justin Reese, Martina Škopková and Chris Mungall and has published in prestigious journals such as SHILAP Revista de lepidopterología, Bioinformatics and PLoS ONE.

In The Last Decade

Daniel Daniš

27 papers receiving 357 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Daniš United States 12 202 189 46 38 32 29 363
Garðar Sveinbjörnsson Iceland 9 184 0.9× 146 0.8× 17 0.4× 23 0.6× 20 0.6× 9 477
Emily A. King United States 4 241 1.2× 171 0.9× 25 0.5× 10 0.3× 13 0.4× 6 417
Lora Ziyabari United States 3 220 1.1× 122 0.6× 75 1.6× 21 0.6× 7 0.2× 4 350
Christine Mundlos Germany 6 256 1.3× 236 1.2× 31 0.7× 75 2.0× 14 0.4× 14 396
Wei-Yang Bai China 10 177 0.9× 95 0.5× 40 0.9× 9 0.2× 11 0.3× 13 339
Michelle Y. Y. Lee United States 10 210 1.0× 79 0.4× 37 0.8× 18 0.5× 105 3.3× 12 374
Nataliya Sharopova United States 3 212 1.0× 114 0.6× 77 1.7× 20 0.5× 7 0.2× 3 333
Bing Gao China 12 320 1.6× 16 0.1× 184 4.0× 15 0.4× 22 0.7× 26 434
Masato Kimura United States 2 205 1.0× 111 0.6× 74 1.6× 21 0.6× 7 0.2× 2 324

Countries citing papers authored by Daniel Daniš

Since Specialization
Citations

This map shows the geographic impact of Daniel Daniš'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 Daniš with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Daniš more than expected).

Fields of papers citing papers by Daniel Daniš

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Daniš. 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 Daniš. The network helps show where Daniel Daniš may publish in the future.

Co-authorship network of co-authors of Daniel Daniš

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Daniš. A scholar is included among the top collaborators of Daniel Daniš 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 Daniš. Daniel Daniš is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Sander, Stanley P., Sophie Anne Inès Klopfenstein, Daniel Daniš, et al.. (2025). An ontology-based rare disease common data model harmonising international registries, FHIR, and Phenopackets. Scientific Data. 12(1). 234–234.
2.
Beckwith, Martha A., et al.. (2024). Leveraging clinical intuition to improve accuracy of phenotype-driven prioritization. Genetics in Medicine. 27(1). 101292–101292.
3.
Karlebach, Guy, Robin Steinhaus, Daniel Daniš, et al.. (2024). Alternative splicing is coupled to gene expression in a subset of variably expressed genes. npj Genomic Medicine. 9(1). 54–54. 5 indexed citations
4.
Jiravský, Otakar, et al.. (2024). Sarcopenia and adipose tissue evaluation by artificial intelligence predicts the overall survival after TAVI. Scientific Reports. 14(1). 8842–8842. 4 indexed citations
5.
Groza, Tudor, Honghan Wu, Marcel E. Dinger, et al.. (2023). Term-BLAST-like alignment tool for concept recognition in noisy clinical texts. Bioinformatics. 39(12). 3 indexed citations
6.
Sundaramurthi, Jagadish Chandrabose, Anita Bagley, Hannah Blau, et al.. (2023). De novoTRPM3missense variant associated with neurodevelopmental delay and manifestations of cerebral palsy. Molecular Case Studies. 9(4). a006293–a006293. 1 indexed citations
7.
Daniš, Daniel, Julius O.B. Jacobsen, Alex H. Wagner, et al.. (2023). Phenopacket-tools: Building and validating GA4GH Phenopackets. PLoS ONE. 18(5). e0285433–e0285433. 4 indexed citations
8.
Jacobsen, Julius O.B., Catherine Kelly, Valentina Cipriani, et al.. (2022). Phenotype‐driven approaches to enhance variant prioritization and diagnosis of rare disease. Human Mutation. 43(8). 1071–1081. 27 indexed citations
9.
Daniš, Daniel, Julius O.B. Jacobsen, Parithi Balachandran, et al.. (2022). SvAnna: efficient and accurate pathogenicity prediction of coding and regulatory structural variants in long-read genome sequencing. Genome Medicine. 14(1). 44–44. 16 indexed citations
10.
Daniš, Daniel, Julius O.B. Jacobsen, Leigh Carmody, et al.. (2021). Interpretable prioritization of splice variants in diagnostic next-generation sequencing. The American Journal of Human Genetics. 108(9). 1564–1577. 30 indexed citations
11.
Petrini, Alessandro, Marco Mesiti, Max Schubach, et al.. (2020). parSMURF, a high-performance computing tool for the genome-wide detection of pathogenic variants. GigaScience. 9(5). 9 indexed citations
12.
Robinson, Peter N., Vida Ravanmehr, Julius O.B. Jacobsen, et al.. (2020). Interpretable Clinical Genomics with a Likelihood Ratio Paradigm. The American Journal of Human Genetics. 107(3). 403–417. 51 indexed citations
13.
Karlebach, Guy, Diogo F. T. Veiga, Robin Steinhaus, et al.. (2020). HBA-DEALS: accurate and simultaneous identification of differential expression and splicing using hierarchical Bayesian analysis. Genome biology. 21(1). 171–171. 6 indexed citations
14.
Carmody, Leigh, Hannah Blau, Daniel Daniš, et al.. (2020). Significantly different clinical phenotypes associated with mutations in synthesis and transamidase+remodeling glycosylphosphatidylinositol (GPI)-anchor biosynthesis genes. Orphanet Journal of Rare Diseases. 15(1). 40–40. 20 indexed citations
15.
Varga, Lukáš, Daniel Daniš, Martina Škopková, et al.. (2020). Novel variants in EDNRB gene in Waardenburg syndrome type II and SOX10 gene in PCWH syndrome. International Journal of Pediatric Otorhinolaryngology. 140. 110499–110499. 4 indexed citations
16.
Varga, Lukáš, et al.. (2019). Novel EYA4 variant in Slovak family with late onset autosomal dominant hearing loss: a case report. BMC Medical Genetics. 20(1). 84–84. 8 indexed citations
17.
Kolníková, Miriam, Martina Škopková, Denisa Ilenčíková, et al.. (2018). DNM1 encephalopathy − atypical phenotype with hypomyelination due to a novel de novo variant in the DNM1 gene. Seizure. 56. 31–33. 17 indexed citations
18.
Staník, Juraj, Martina Škopková, Daniel Daniš, et al.. (2017). Congenital hyperinsulinism and glycogenosis-like phenotype due to a novel HNF4A mutation. Diabetes Research and Clinical Practice. 126. 144–150. 12 indexed citations
19.
Škopková, Martina, Miriam Čiljaková, Daniel Daniš, et al.. (2016). Two novel RFX6 variants in siblings with Mitchell-Riley syndrome with later diabetes onset and heterotopic gastric mucosa. European Journal of Medical Genetics. 59(9). 429–435. 11 indexed citations
20.
Gazdíková, Katarína, et al.. (2012). [Virological sustained response to former young intravenous drug abusers with chronic hepatitis C treated by pegylated interferon-α plus ribavirin].. PubMed. 58(2). 104–9. 1 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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