Lit‐Hsin Loo

2.0k total citations · 1 hit paper
33 papers, 1.2k citations indexed

About

Lit‐Hsin Loo is a scholar working on Molecular Biology, Biophysics and Oncology. According to data from OpenAlex, Lit‐Hsin Loo has authored 33 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 12 papers in Biophysics and 6 papers in Oncology. Recurrent topics in Lit‐Hsin Loo's work include Cell Image Analysis Techniques (12 papers), Single-cell and spatial transcriptomics (8 papers) and Computational Drug Discovery Methods (6 papers). Lit‐Hsin Loo is often cited by papers focused on Cell Image Analysis Techniques (12 papers), Single-cell and spatial transcriptomics (8 papers) and Computational Drug Discovery Methods (6 papers). Lit‐Hsin Loo collaborates with scholars based in Singapore, United States and Italy. Lit‐Hsin Loo's co-authors include Lani F. Wu, Steven J. Altschuler, Alvin Wei Tian Ng, Evelyn Wong, Sunny H. Wong, Joanne Ngeow, Ming Ren Toh, Daniele Zink, Ran Su and Sijing Xiong and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and The Journal of Cell Biology.

In The Last Decade

Lit‐Hsin Loo

31 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.

Global Epidemiology and Genetics of Hepatocellular Carcinoma

2023 292 citations Ming Ren Toh, Evelyn Wong et al. Gastroenterology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Lit‐Hsin Loo Singapore	14	601	366	171	139	134	33	1.2k
Dolores Diaz United States	15	618 1.0×	72 0.2×	259 1.5×	143 1.0×	203 1.5×	22	1.3k
Jordi Carreras‐Puigvert Sweden	18	445 0.7×	124 0.3×	172 1.0×	51 0.4×	85 0.6×	33	750
Sonja Sievers Germany	27	1.2k 1.9×	191 0.5×	179 1.0×	59 0.4×	187 1.4×	93	2.0k
Mark E. Schurdak United States	25	1.0k 1.7×	64 0.2×	182 1.1×	151 1.1×	97 0.7×	48	1.7k
Marc Hafner United States	19	1.2k 2.0×	173 0.5×	467 2.7×	168 1.2×	470 3.5×	58	2.0k
Jorrit J. Hornberg Netherlands	18	812 1.4×	69 0.2×	147 0.9×	112 0.8×	234 1.7×	29	1.3k
Joshua A. Bittker United States	16	589 1.0×	91 0.2×	61 0.4×	60 0.4×	140 1.0×	31	909
Mirra Chung United States	20	949 1.6×	86 0.2×	544 3.2×	76 0.5×	167 1.2×	29	1.8k
Octavian Bucur United States	18	878 1.5×	162 0.4×	273 1.6×	106 0.8×	25 0.2×	43	1.4k
Nehmé El-Hachem Canada	19	892 1.5×	87 0.2×	297 1.7×	140 1.0×	378 2.8×	50	1.9k

Countries citing papers authored by Lit‐Hsin Loo

Since Specialization

Citations

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

Fields of papers citing papers by Lit‐Hsin Loo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lit‐Hsin Loo. 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 Lit‐Hsin Loo. The network helps show where Lit‐Hsin Loo may publish in the future.

Co-authorship network of co-authors of Lit‐Hsin Loo

This figure shows the co-authorship network connecting the top 25 collaborators of Lit‐Hsin Loo. A scholar is included among the top collaborators of Lit‐Hsin Loo 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 Lit‐Hsin Loo. Lit‐Hsin Loo 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

Friedman, Katie Paul, Russell S. Thomas, John F. Wambaugh, et al.. (2025). Integration of new approach methods for the assessment of data-poor chemicals. Toxicological Sciences. 205(1). 74–105. 8 indexed citations

Wu, Xiaofeng, Weize Xu, Leqiang Sun, et al.. (2025). The application and prospects of spatial omics technologies in clinical medical research and molecular diagnostics. Journal of genetics and genomics. 53(2). 181–196.

Zhang, Yanlong, Chin Wee Tan, Yang Wu, et al.. (2024). Spatial omics techniques and data analysis for cancer immunotherapy applications. Current Opinion in Biotechnology. 87. 103111–103111. 11 indexed citations

Toh, Ming Ren, Evelyn Wong, Sunny H. Wong, et al.. (2023). Global Epidemiology and Genetics of Hepatocellular Carcinoma. Gastroenterology. 164(5). 766–782. 292 indexed citations breakdown →

Yeong, Joe, Huey Yew Jeffrey Lum, Chong Boon Teo, et al.. (2022). Choice of PD-L1 immunohistochemistry assay influences clinical eligibility for gastric cancer immunotherapy. Gastric Cancer. 25(4). 741–750. 67 indexed citations

Tan, Benedict, et al.. (2021). Leveraging advances in immunopathology and artificial intelligence to analyze in vitro tumor models in composition and space. Advanced Drug Delivery Reviews. 177. 113959–113959. 11 indexed citations

Maurer‐Stroh, Sebastian, et al.. (2021). Structure-based virtual screening of CYP1A1 inhibitors: towards rapid tier-one assessment of potential developmental toxicants. Archives of Toxicology. 95(9). 3031–3048. 9 indexed citations

Basu, Sreetama, et al.. (2020). Predicting direct hepatocyte toxicity in humans by combining high-throughput imaging of HepaRG cells and machine learning-based phenotypic profiling. Archives of Toxicology. 94(8). 2749–2767. 13 indexed citations

Jaladanki, Chaitanya K., Yang He, Li Na Zhao, et al.. (2020). Virtual screening of potentially endocrine-disrupting chemicals against nuclear receptors and its application to identify PPARγ-bound fatty acids. Archives of Toxicology. 95(1). 355–374. 13 indexed citations

10.

Loo, Lit‐Hsin, et al.. (2020). Optimum concentration–response curve metrics for supervised selection of discriminative cellular phenotypic endpoints for chemical hazard assessment. Archives of Toxicology. 94(9). 2951–2964. 2 indexed citations

11.

Bougen‐Zhukov, Nicola, et al.. (2019). PI3K Catalytic Subunits α and β Modulate Cell Death and IL-6 Secretion Induced by Talc Particles in Human Lung Carcinoma Cells. American Journal of Respiratory Cell and Molecular Biology. 62(3). 331–341. 2 indexed citations

12.

Basu, Sreetama, et al.. (2018). Building predictive in vitro pulmonary toxicity assays using high-throughput imaging and artificial intelligence. Archives of Toxicology. 92(6). 2055–2075. 21 indexed citations

13.

Loo, Lit‐Hsin, et al.. (2017). Early spatiotemporal-specific changes in intermediate signals are predictive of cytotoxic sensitivity to TNFα and co-treatments. Scientific Reports. 7(1). 43541–43541. 6 indexed citations

14.

Su, Ran, Sijing Xiong, Daniele Zink, & Lit‐Hsin Loo. (2015). High-throughput imaging-based nephrotoxicity prediction for xenobiotics with diverse chemical structures. Archives of Toxicology. 90(11). 2793–2808. 49 indexed citations

15.

Kandasamy, Karthikeyan, Ran Su, Sijing Xiong, et al.. (2015). Prediction of drug-induced nephrotoxicity and injury mechanisms with human induced pluripotent stem cell-derived cells and machine learning methods. Scientific Reports. 5(1). 12337–12337. 78 indexed citations

16.

Loo, Lit‐Hsin, et al.. (2014). Quantitative Protein Localization Signatures Reveal an Association between Spatial and Functional Divergences of Proteins. PLoS Computational Biology. 10(3). e1003504–e1003504. 25 indexed citations

17.

Loo, Lit‐Hsin, et al.. (2009). An approach for extensibly profiling the molecular states of cellular subpopulations. Nature Methods. 6(10). 759–765. 57 indexed citations

18.

Loo, Lit‐Hsin, et al.. (2007). New criteria for selecting differentially expressed genes. IEEE Engineering in Medicine and Biology Magazine. 26(2). 17–26. 6 indexed citations

19.

Loo, Lit‐Hsin, Lani F. Wu, & Steven J. Altschuler. (2007). Image-based multivariate profiling of drug responses from single cells. Nature Methods. 4(5). 445–453. 261 indexed citations

20.

Loo, Lit‐Hsin, Lani F. Wu, & Steven J. Altschuler. (2006). Automated Multivariate Profiling of Drug Effects from Fluorescence Microscopy Images. 1. 251–254. 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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