Lee-kai Wang

1.8k total citations · 1 hit paper
5 papers, 299 citations indexed

About

Lee-kai Wang is a scholar working on Molecular Biology, Cognitive Neuroscience and Genetics. According to data from OpenAlex, Lee-kai Wang has authored 5 papers receiving a total of 299 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Molecular Biology, 2 papers in Cognitive Neuroscience and 2 papers in Genetics. Recurrent topics in Lee-kai Wang's work include Congenital heart defects research (2 papers), HIV Research and Treatment (1 paper) and Genetic Associations and Epidemiology (1 paper). Lee-kai Wang is often cited by papers focused on Congenital heart defects research (2 papers), HIV Research and Treatment (1 paper) and Genetic Associations and Epidemiology (1 paper). Lee-kai Wang collaborates with scholars based in United States, Slovenia and United Kingdom. Lee-kai Wang's co-authors include Laura Pérez‐Cano, Michael J. Gandal, Jennifer K. Lowe, Kelley Paskov, David A. Prober, Nate Stockham, Dorna Kashef-Haghighi, Daniel H. Geschwind, Virpi Leppä and Damon Polioudakis and has published in prestigious journals such as Cell, Nature Neuroscience and International Journal of Molecular Sciences.

In The Last Decade

Lee-kai Wang

4 papers receiving 296 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.

Inherited and De Novo Genetic Risk for Autism Impacts Shared Networks

2019 257 citations Elizabeth K. Ruzzo, Laura Pérez‐Cano et al. Cell profile →

Peers

Lee-kai Wang

GENET

MB

CN

CMN

CB

Christine Ochoa Escamilla United States

Anke Van Dijck Belgium

Stephanie M. Kyle United States

Marat Mufteev Canada

Pan Zhang China

Hannah M. Grayton United Kingdom

Carrie Wright United States

Atsuki Kawamura Japan

Samuel W. Hulbert United States

Mary Jacena Leigh United States

Christine Ochoa Escamilla United States

Lee-kai Wang

176 ×1.1

GENET

168 ×1.0

MB

131 ×0.9

CN

49 ×1.9

CMN

30 ×1.2

CB

Citations per year, relative to Lee-kai Wang Lee-kai Wang (= 1×) peers Christine Ochoa Escamilla

Countries citing papers authored by Lee-kai Wang

Since Specialization

Citations

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

Fields of papers citing papers by Lee-kai Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lee-kai Wang. 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 Lee-kai Wang. The network helps show where Lee-kai Wang may publish in the future.

Co-authorship network of co-authors of Lee-kai Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Lee-kai Wang. A scholar is included among the top collaborators of Lee-kai Wang 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 Lee-kai Wang. Lee-kai Wang 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:

5 of 5 papers shown

1.

Kang, Xuedong, Lee-kai Wang, Reshma Biniwale, et al.. (2025). Whole-Exome Sequencing Identifies Novel GATA5/6 Variants in Right-Sided Congenital Heart Defects. International Journal of Molecular Sciences. 26(5). 2115–2115.

2.

Kim, Minsoo, Jillian R. Haney, Pan Zhang, et al.. (2021). Brain gene co-expression networks link complement signaling with convergent synaptic pathology in schizophrenia. Nature Neuroscience. 24(6). 799–809. 39 indexed citations

3.

Ruzzo, Elizabeth K., Laura Pérez‐Cano, Jae-Yoon Jung, et al.. (2019). Inherited and De Novo Genetic Risk for Autism Impacts Shared Networks. Cell. 178(4). 850–866.e26. 257 indexed citations breakdown →

4.

Ruzzo, Elizabeth K., Laura Pérez‐Cano, Jae-Yoon Jung, et al.. (2019). INHERITED AND DE NOVO GENETIC RISK FOR AUTISM IMPACTS SHARED BIOLOGICAL NETWORKS. European Neuropsychopharmacology. 29. S35–S36. 2 indexed citations

5.

Rubinsteyn, Alex, Tavi Nathanson, Arun Ahuja, et al.. (2017). hammerlab/varcode: Version 0.5.15. Zenodo (CERN European Organization for Nuclear Research). 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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