Cheng‐Yan Kao

1.5k total citations
66 papers, 954 citations indexed

About

Cheng‐Yan Kao is a scholar working on Molecular Biology, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Cheng‐Yan Kao has authored 66 papers receiving a total of 954 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Molecular Biology, 17 papers in Artificial Intelligence and 15 papers in Computational Theory and Mathematics. Recurrent topics in Cheng‐Yan Kao's work include Gene expression and cancer classification (13 papers), Bioinformatics and Genomic Networks (13 papers) and Metaheuristic Optimization Algorithms Research (11 papers). Cheng‐Yan Kao is often cited by papers focused on Gene expression and cancer classification (13 papers), Bioinformatics and Genomic Networks (13 papers) and Metaheuristic Optimization Algorithms Research (11 papers). Cheng‐Yan Kao collaborates with scholars based in Taiwan, United States and Canada. Cheng‐Yan Kao's co-authors include Feng‐Tse Lin, Ching‐Chi Hsu, Jinn‐Moon Yang, Jorng‐Tzong Horng, Huai‐Kuang Tsai, Chen‐hsiung Chan, Chi‐Hung Tsai, Han Lin, Chi‐Ying F. Huang and D. Frank Hsu and has published in prestigious journals such as Bioinformatics, PLoS ONE and International Journal of Molecular Sciences.

In The Last Decade

Cheng‐Yan Kao

62 papers receiving 882 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Cheng‐Yan Kao Taiwan	17	426	211	150	132	125	66	954
Martyn Amos United Kingdom	17	445 1.0×	253 1.2×	154 1.0×	106 0.8×	93 0.7×	70	982
Kunihiko Hiraishi Japan	14	302 0.7×	68 0.3×	222 1.5×	78 0.6×	155 1.2×	113	753
Michael A. Lones United Kingdom	17	207 0.5×	353 1.7×	76 0.5×	29 0.2×	90 0.7×	63	893
Binhai Zhu United States	16	156 0.4×	159 0.8×	121 0.8×	43 0.3×	128 1.0×	122	883
Luca Manzoni Italy	17	476 1.1×	568 2.7×	278 1.9×	36 0.3×	59 0.5×	115	1.1k
Sebastian Wernicke Germany	13	480 1.1×	166 0.8×	280 1.9×	22 0.2×	96 0.8×	35	1.1k
Sairam Subramanian United States	11	356 0.8×	156 0.7×	350 2.3×	25 0.2×	284 2.3×	16	975
Marco Tomassini Switzerland	16	184 0.4×	741 3.5×	300 2.0×	45 0.3×	66 0.5×	52	1.0k
Paola Bertolazzi Italy	17	404 0.9×	152 0.7×	118 0.8×	15 0.1×	60 0.5×	54	981
Vı́ctor Robles Spain	15	579 1.4×	691 3.3×	173 1.2×	45 0.3×	73 0.6×	41	1.6k

Countries citing papers authored by Cheng‐Yan Kao

Since Specialization

Citations

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

Fields of papers citing papers by Cheng‐Yan Kao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cheng‐Yan Kao. 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 Cheng‐Yan Kao. The network helps show where Cheng‐Yan Kao may publish in the future.

Co-authorship network of co-authors of Cheng‐Yan Kao

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Chu, Hsueh‐Ting, Han Lin, William Hsiao, et al.. (2013). Genotyping of human neutrophil antigens (HNA) from whole genome sequencing data. BMC Medical Genomics. 6(1). 31–31. 5 indexed citations

Chu, Hsueh‐Ting, et al.. (2013). SeqEntropy: Genome-Wide Assessment of Repeats for Short Read Sequencing. PLoS ONE. 8(3). e59484–e59484. 3 indexed citations

Chu, Hsueh‐Ting, William Hsiao, Ching‐Mao Chang, et al.. (2012). Quantitative assessment of mitochondrial DNA copies from whole genome sequencing. BMC Genomics. 13(S7). S5–S5. 22 indexed citations

Liu, Chia-Hung, Han Lin, Chi‐Ying F. Huang, et al.. (2012). A Multiclass Classification Tool Using Cloud Computing Architecture. 25. 765–770. 6 indexed citations

Lee, Sheng‐An, Chen‐hsiung Chan, Yue‐Li Juang, et al.. (2009). Cliques in mitotic spindle network bring kinetochore‐associated complexes to form dependence pathway. PROTEOMICS. 9(16). 4048–4062. 11 indexed citations

Kao, Cheng‐Yan, et al.. (2007). Modeling Taiwanese Southern-Min Tone Sandhi Using Rule-Based Methods. 12(4). 349–370.

Lin, Chung‐Yen, et al.. (2007). Reconstruction of human protein interolog network using evolutionary conserved network. BMC Bioinformatics. 8(1). 152–152. 28 indexed citations

Tsai, Chi‐Hung, Chen‐hsiung Chan, Bo‐Juen Chen, et al.. (2007). Bioinformatics Approaches for Disulfide Connectivity Prediction. Current Protein and Peptide Science. 8(3). 243–260. 13 indexed citations

Chiu, Hua‐Sheng, et al.. (2004). Discovering Statistically Significant Clusters by Using Iterative Genetic Algorithms in Gene Expression Data.. 243–249. 1 indexed citations

10.

Tien, An‐Chi, et al.. (2004). POINT: a database for the prediction of protein–protein interactions based on the orthologous interactome. Bioinformatics. 20(17). 3273–3276. 80 indexed citations

11.

Chuang, Han‐Yu, et al.. (2003). Ranking Genes for Discriminability on Microarray Data. Journal of information science and engineering. 19. 953–966. 6 indexed citations

12.

Tsai, Huai‐Kuang, Jinn‐Moon Yang, & Cheng‐Yan Kao. (2002). Applying Genetic Algorithms To Finding The Optimal Gene Order In Displaying The Microarray Data. Genetic and Evolutionary Computation Conference. 610–617. 11 indexed citations

13.

Yang, Jinn‐Moon, et al.. (2002). GEM: A Gaussian evolutionary method for predicting protein side‐chain conformations. Protein Science. 11(8). 1897–1907. 16 indexed citations

14.

Kao, Cheng‐Yan, et al.. (2002). Molecular binding: a case study of the population-based annealing genetic algorithms. 1. 50–50. 6 indexed citations

15.

Tsai, Huai‐Kuang, Jinn‐Moon Yang, & Cheng‐Yan Kao. (2001). A genetic algorithm for traveling salesman problems. Genetic and Evolutionary Computation Conference. 687–693. 21 indexed citations

16.

Horng, Jorng‐Tzong, et al.. (2001). Solving fixed channel assignment problems by an evolutionary approach. Genetic and Evolutionary Computation Conference. 351–358. 2 indexed citations

17.

Horng, Jorng‐Tzong, et al.. (2001). Mining Putative Regulatory Elements in Gene Promoter Regions.. 90–95. 6 indexed citations

18.

Yang, Jinn‐Moon & Cheng‐Yan Kao. (2000). An evolutionary algorithm to training neural networks for a two-spiral problem. Genetic and Evolutionary Computation Conference. 1025–1032. 2 indexed citations

19.

Yang, Jinn‐Moon & Cheng‐Yan Kao. (2000). A family competition evolutionary algorithm for automated docking of flexible ligands to proteins. IEEE Transactions on Information Technology in Biomedicine. 4(3). 225–237. 13 indexed citations

20.

Yang, Jinn‐Moon, Jorng‐Tzong Horng, & Cheng‐Yan Kao. (1997). A Continuous Genetic Algorithm for Global Optimization.. 50(580). 230–237. 12 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.

Explore authors with similar magnitude of impact