Lisa Ta

713 total citations
9 papers, 263 citations indexed

About

Lisa Ta is a scholar working on Biomedical Engineering, Molecular Biology and Genetics. According to data from OpenAlex, Lisa Ta has authored 9 papers receiving a total of 263 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Biomedical Engineering, 3 papers in Molecular Biology and 3 papers in Genetics. Recurrent topics in Lisa Ta's work include Glioma Diagnosis and Treatment (3 papers), Medical Imaging Techniques and Applications (2 papers) and 3D Printing in Biomedical Research (2 papers). Lisa Ta is often cited by papers focused on Glioma Diagnosis and Treatment (3 papers), Medical Imaging Techniques and Applications (2 papers) and 3D Printing in Biomedical Research (2 papers). Lisa Ta collaborates with scholars based in United States and Germany. Lisa Ta's co-authors include David A. Nathanson, Ken Herrmann, Johannes Czernin, Jesse Liang, Alireza Sohrabi, Arshia Ehsanipour, Weikun Xiao, Christopher M. Walthers, Rongyu Zhang and Stephanie K. Seidlits and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Medicine and Cancer Research.

In The Last Decade

Lisa Ta

8 papers receiving 258 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Lisa Ta United States	6	98	86	64	63	55	9	263
Christina Schug Germany	14	174 1.8×	71 0.8×	62 1.0×	43 0.7×	61 1.1×	15	347
Billy Samuel Hill Italy	6	182 1.9×	177 2.1×	46 0.7×	87 1.4×	59 1.1×	7	341
Gergő Kiszner Hungary	10	185 1.9×	85 1.0×	91 1.4×	46 0.7×	19 0.3×	13	373
Simon Khagi United States	9	101 1.0×	113 1.3×	72 1.1×	45 0.7×	110 2.0×	28	325
Roman Reinartz Germany	5	89 0.9×	49 0.6×	23 0.4×	55 0.9×	129 2.3×	5	242
Prospero Civita Italy	10	123 1.3×	62 0.7×	51 0.8×	58 0.9×	78 1.4×	16	301
Ivett Teleki Hungary	8	205 2.1×	80 0.9×	88 1.4×	48 0.8×	18 0.3×	10	372
Hitomi Hosoya United States	9	69 0.7×	90 1.0×	32 0.5×	15 0.2×	31 0.6×	24	238
Henrik Schinke Germany	4	162 1.7×	141 1.6×	48 0.8×	75 1.2×	12 0.2×	6	299
Valentina Robila United States	10	153 1.6×	129 1.5×	21 0.3×	64 1.0×	38 0.7×	25	359

Countries citing papers authored by Lisa Ta

Since Specialization

Citations

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

Fields of papers citing papers by Lisa Ta

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lisa Ta. 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 Lisa Ta. The network helps show where Lisa Ta may publish in the future.

Co-authorship network of co-authors of Lisa Ta

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

9 of 9 papers shown

1.

Bangayan, Nathanael J., Liang Wang, Donghui Cheng, et al.. (2023). Dual-inhibitory domain iCARs improve the efficiency of the AND-NOT gate CAR T strategy. Proceedings of the National Academy of Sciences. 120(47). e2312374120–e2312374120. 29 indexed citations

2.

Bayley, Nicholas, Henan Zhu, Weihong Yan, et al.. (2022). TMIC-40. TRANSCRIPTOMIC CHARACTERIZATION OF PATIENT GLIOMAS AND DERIVED MODEL SYSTEMS REVEALS ENVIRONMENTAL INFLUENCE ON NEURODEVELOPMENTAL CELLULAR STATES. Neuro-Oncology. 24(Supplement_7). vii280–vii280.

3.

Ta, Lisa, et al.. (2018). Processing of Primary Patient Tumors and Subsequent Generation of Primary Cell Lines. Methods in molecular biology. 1897. 425–431. 4 indexed citations

4.

Ta, Lisa, et al.. (2018). Biosafety and Biohazards: Understanding Biosafety Levels and Meeting Safety Requirements of a Biobank. Methods in molecular biology. 1897. 213–225. 21 indexed citations

5.

Xiao, Weikun, Rongyu Zhang, Alireza Sohrabi, et al.. (2017). Brain-Mimetic 3D Culture Platforms Allow Investigation of Cooperative Effects of Extracellular Matrix Features on Therapeutic Resistance in Glioblastoma. Cancer Research. 78(5). 1358–1370. 69 indexed citations

6.

Wilson, X., Veerle W. Daniëls, Lisa Ta, et al.. (2017). Cytoplasmic p53 couples oncogene-driven glucose metabolism to apoptosis and is a therapeutic target in glioblastoma. Nature Medicine. 23(11). 1342–1351. 84 indexed citations

7.

Laks, Dan R., Lisa Ta, Thomas J. Crisman, et al.. (2016). Inhibition of Nucleotide Synthesis Targets Brain Tumor Stem Cells in a Subset of Glioblastoma. Molecular Cancer Therapeutics. 15(6). 1271–1278. 12 indexed citations

8.

Shin, Young Shik, Jung-Woo Kim, Alex A. Dooraghi, et al.. (2015). Quantitative assessments of glycolysis from single cells. PubMed. 3(4). 172–178. 3 indexed citations

9.

Czernin, Johannes, Lisa Ta, & Ken Herrmann. (2014). Does PET/MR Imaging Improve Cancer Assessments? Literature Evidence from More Than 900 Patients. Journal of Nuclear Medicine. 55(Supplement 2). 59S–62S. 41 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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