Weng-Long Chang

834 total citations
51 papers, 560 citations indexed

About

Weng-Long Chang is a scholar working on Molecular Biology, Computational Theory and Mathematics and Artificial Intelligence. According to data from OpenAlex, Weng-Long Chang has authored 51 papers receiving a total of 560 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 20 papers in Computational Theory and Mathematics and 19 papers in Artificial Intelligence. Recurrent topics in Weng-Long Chang's work include DNA and Biological Computing (21 papers), Advanced biosensing and bioanalysis techniques (17 papers) and Quantum Computing Algorithms and Architecture (14 papers). Weng-Long Chang is often cited by papers focused on DNA and Biological Computing (21 papers), Advanced biosensing and bioanalysis techniques (17 papers) and Quantum Computing Algorithms and Architecture (14 papers). Weng-Long Chang collaborates with scholars based in Taiwan, Japan and China. Weng-Long Chang's co-authors include Minyi Guo, Michael Ho, Athanasios V. Vasilakos, Chih‐Ping Chu, Mang Feng, Kawuu W. Lin, Wen‐Shiung Lour, Ju-Chin Chen, Wen‐Yu Chung and J. L. Luo and has published in prestigious journals such as Scientific Reports, IEEE Electron Device Letters and Electronics Letters.

In The Last Decade

Weng-Long Chang

48 papers receiving 517 citations

Peers

Countries citing papers authored by Weng-Long Chang

Since Specialization

Citations

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

Fields of papers citing papers by Weng-Long Chang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Weng-Long Chang. 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 Weng-Long Chang. The network helps show where Weng-Long Chang may publish in the future.

Co-authorship network of co-authors of Weng-Long Chang

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

All Works

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20 of 20 papers shown

#	Title	Journal	Authors	Indexed citations
1	Biomolecular and quantum algorithms for the dominating set problem in arbitrary networks	Scientific Reports	Weng-Long Chang, Wen‐Yu Chung et al.	5
2	Quantum Speedup and Mathematical Solutions of Implementing Bio-Molecular Solutions for the Independent Set Problem on IBM Quantum Computers	IEEE Transactions on NanoBioscience	Weng-Long Chang, Ju-Chin Chen et al.	22
3	Molecular Computing		Weng-Long Chang, Athanasios V. Vasilakos	8
4	Fast Parallel DNA-Based Algorithms for Molecular Computation: Quadratic Congruence and Factoring Integers	IEEE Transactions on NanoBioscience	Weng-Long Chang	15
5	Molecular solutions of the RSA public-key cryptosystem on a DNA-based computer	The Journal of Supercomputing	Weng-Long Chang, Kawuu W. Lin et al.	14
6	Fast Quantum Algorithms of Breaking the Data Encryption Standard		Weng-Long Chang	1
7	Fast parallel DNA-based algorithms for molecular computation: discrete logarithm	The Journal of Supercomputing	Weng-Long Chang, Kawuu W. Lin et al.	16
8	Quantum Algorithms for Biomolecular Solutions of the Satisfiability Problem on a Quantum Machine	IEEE Transactions on NanoBioscience	Weng-Long Chang, Tingting Ren et al.	20
9	Fast Parallel DNA-Based Algorithms for Molecular Computation: The Set-Partition Problem	IEEE Transactions on NanoBioscience	Weng-Long Chang	24
10	Fast Parallel Molecular Algorithms for DNA-Based Computation: Factoring Integers	IEEE Transactions on NanoBioscience	Weng-Long Chang, Minyi Guo et al.	67
11	Fast Parallel DNA-Based Algorithms for Molecular Computation: Determining a Prime Number		Weng-Long Chang, Minyi Guo et al.	2
12	Fast Parallel Solution for Set-Packing and Clique Problems by DNA-Based Computing	IEICE Transactions on Information and Systems	Michael Ho, Weng-Long Chang et al.	7
13	Molecular solutions for the subset-sum problem on DNA-based supercomputing	Biosystems	Weng-Long Chang, Michael Ho et al.	45
14	Fast parallel molecular solution to the dominating-set problem on massively parallel bio-computing	Parallel Computing	Minyi Guo, Michael Ho et al.	25
15	The non-continuous direction vector I test		Minyi Guo, Weng-Long Chang et al.	1
16	Solving the Set-Splitting Problem in Sticker-Based Model and the Adleman-Lipton Model.		Weng-Long Chang, Minyi Guo et al.	6
17	Solving the set-splitting problem in sticker-based model and the lipton-adelmann model		Weng-Long Chang, Minyi Guo et al.	1
18	Efficient loop partitioning for parallel codes of irregular scientific computations		Minyi Guo, Li Li et al.	2
19	The generalized Direction Vector I test	Parallel Computing	Weng-Long Chang, Chih‐Ping Chu	8
20	Investigation of an AlInAs/GaInAs superlattice-emitter resonant tunneling bipolar transistor (SE-RTBT)	Superlattices and Microstructures	Cheng Shen, Weng-Long Chang et al.	1

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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