Max K. Leong

1.5k citations

40 papers · 1.2k indexed · 1 hit paper · h-index 21

Molecular Biology
Computational Theory and Mathematics top 2%
Organic Chemistry top 10%
Oncology
Pharmacology top 5%

Co-authors: Ching‐Feng Weng Shian‐Ren Lin Ping‐Jyun Sung Henrich Cheng Che‐Fang Hsu Jian‐Chyi Chen V. S. Mastryukov James E. Boggs
Topics: Computational Drug Discovery Methods (16 papers)Analytical Chemistry and Chromatography (5 papers)Drug Transport and Resistance Mechanisms (5 papers)
Cited by: Computational Theory and Mathematics Pharmacology Pharmaceutical Science
Journals: SHILAP Revista de lepidopterologíaPLoS ONE The Journal of Physical Chemistry
Partner nations: Taiwan Vietnam China

In The Last Decade

Max K. Leong

39 papers receiving 1.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Natural compounds as potential adjuvants to cancer therapy: Preclinical evidence

2019 304 citations Shian‐Ren Lin, Max K. Leong et al. profile →

Peers

Countries citing papers authored by Max K. Leong

Since Specialization

Citations

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

Fields of papers citing papers by Max K. Leong

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Max K. Leong. 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 Max K. Leong. The network helps show where Max K. Leong may publish in the future.

Co-authorship network of co-authors of Max K. Leong

This figure shows the co-authorship network connecting the top 25 collaborators of Max K. Leong. A scholar is included among the top collaborators of Max K. Leong 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 Max K. Leong. Max K. Leong 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

#	Work	Indexed citations
1	Modeling skin sensitization: hierarchical support vector regression−based prediction of lysine depletion in DPRA 2025 ·Chemico-Biological Interactions ·(unknown),Max K. Leong	1
2	A novel in silico approach for predicting unbound brain-to-plasma ratio using machine learning-based support vector regression 2025 ·Computers in Biology and Medicine ·(unknown),Max K. Leong	0
3	Development of a hierarchical support vector regression-based in silico model for the prediction of the cysteine depletion in DPRA 2024 ·Toxicology ·(unknown),Ching‐Feng Weng,Max K. Leong	3
4	Using Machine Learning-Based Hierarchical Support Vector Regression Approach to Predict Skin Permeability 2022 ·SHILAP Revista de lepidopterología ·Max K. Leong,(unknown)	1
5	In Silico Prediction of Skin Permeability Using a Two-QSAR Approach 2022 ·Pharmaceutics ·(unknown),(unknown),(unknown),Ching‐Feng Weng,Max K. Leong	11
6	Mangosteen xanthone γ-mangostin exerts lowering blood glucose effect with potentiating insulin sensitivity through the mediation of AMPK/PPARγ 2021 ·Biomedicine & Pharmacotherapy ·(unknown),Shian‐Ren Lin,(unknown),Hui Suan Ng,(unknown),Max K. Leong,Ching‐Feng Weng	22
7	In silico Prediction of Skin Sensitization: Quo vadis? 2021 ·Frontiers in Pharmacology ·(unknown),Ching‐Feng Weng,Max K. Leong	28
8	In Silico Approaches to Identify Polyphenol Compounds as α-Glucosidase and α-Amylase Inhibitors against Type-II Diabetes 2021 ·Biomolecules ·(unknown),Dinh‐Chuong Pham,Max K. Leong,Ching‐Feng Weng	96
9	Prediction of N-Methyl-D-Aspartate Receptor GluN1-Ligand Binding Affinity by a Novel SVM-Pose/SVM-Score Combinatorial Ensemble Docking Scheme 2017 ·Scientific Reports ·Max K. Leong,(unknown),(unknown),Ching‐Feng Weng	21
10	Encapsulation of 16-Hydroxycleroda-3,13-Dine-16,15-Olide in Mesoporous Silica Nanoparticles as a Natural Dipeptidyl Peptidase-4 Inhibitor Potentiated Hypoglycemia in Diabetic Mice 2017 ·Nanomaterials ·Po-Kai Huang,(unknown),May‐Jywan Tsai,Max K. Leong,Shian‐Ren Lin,Ranjith Kumar Kankala,Chia‐Hung Lee,Ching‐Feng Weng	30
11	In silico prediction of the mutagenicity of nitroaromatic compounds using a novel two-QSAR approach 2016 ·Toxicology in Vitro ·(unknown),(unknown),Max K. Leong	28
12	In Silico Prediction of Inhibition of Promiscuous Breast Cancer Resistance Protein (BCRP/ABCG2) 2014 ·PLoS ONE ·(unknown),(unknown),Fu‐Yuan Tsai,Max K. Leong	14
13	Prediction of Promiscuous P-Glycoprotein Inhibition Using a Novel Machine Learning Scheme 2012 ·PLoS ONE ·Max K. Leong,Hongbin Chen,(unknown)	22
14	Predicting Mutagenicity of Aromatic Amines by Various Machine Learning Approaches 2010 ·Toxicological Sciences ·Max K. Leong,(unknown),Hongbin Chen,Fu‐Yuan Tsai	33
15	Prediction of Cytochrome P450 2B6-Substrate Interactions Using Pharmacophore Ensemble/Support Vector Machine (PhE/SVM) Approach 2008 ·Medicinal Chemistry ·Max K. Leong,(unknown)	17
16	Prediction of human cytochrome P450 2B6‐substrate interactions using hierarchical support vector regression approach 2008 ·Journal of Computational Chemistry ·Max K. Leong,Yen‐Ming Chen,(unknown)	21
17	Au(i)-benzimidazole/imidazole complexes. Liquid crystals and nanomaterials 2008 ·Dalton Transactions ·(unknown),(unknown),Max K. Leong,Ivan J. B. Lin	40
18	Selection and characterization of lipase abzyme from phage displayed antibody libraries 2007 ·Biochemical and Biophysical Research Communications ·Max K. Leong,Chinpiao Chen,(unknown),David Shiuan	7
19	3D-QSAR studies on PU3 analogues by comparative molecular field analysis 2003 ·Bioorganic & Medicinal Chemistry Letters ·(unknown),Ping‐Chiang Lyu,Max K. Leong,Keng‐Chang Tsai,Ging‐Ho Hsiue	4
20	Application of the Barton photochemical reaction in the synthesis of 1-dethia-3-aza-1-carba-2-oxacephem: a novel agent against resistant pathogenic microorganisms 2003 ·Organic & Biomolecular Chemistry ·G. H. HAKIMELAHI,Pai‐Chi Li,Ali Akbar Moosavi‐Movahedi,Jamshidkhan Chamani,Ghadamali Khodarahmi,Tai Wei Ly,(unknown),Max K. Leong,Shahram Hakimelahi,Kak‐Shan Shia,Ito Chao	12

About Max K. Leong

Max K. Leong is a scholar working on Computational Theory and Mathematics, Applied Microbiology and Biotechnology and Pharmaceutical Science, having authored 40 papers that have together received 1.2k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (16 papers), Analytical Chemistry and Chromatography (5 papers) and Drug Transport and Resistance Mechanisms (5 papers). The work is most often cited by research in Computational Theory and Mathematics (286 citations), Pharmacology (131 citations) and Pharmaceutical Science (61 citations). Max K. Leong has collaborated with scholars based in Taiwan, Vietnam and China. Frequent co-authors include Ching‐Feng Weng, Shian‐Ren Lin, Ping‐Jyun Sung, Henrich Cheng, Che‐Fang Hsu, Jian‐Chyi Chen, V. S. Mastryukov, James E. Boggs, Dinh‐Chuong Pham and Hongbin Chen. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and The Journal of Physical Chemistry.

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