Yingtao Bi

2.5k total citations
41 papers, 1.3k citations indexed

About

Yingtao Bi is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Yingtao Bi has authored 41 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 10 papers in Cancer Research and 7 papers in Genetics. Recurrent topics in Yingtao Bi's work include Glioma Diagnosis and Treatment (7 papers), RNA Research and Splicing (7 papers) and Gene expression and cancer classification (5 papers). Yingtao Bi is often cited by papers focused on Glioma Diagnosis and Treatment (7 papers), RNA Research and Splicing (7 papers) and Gene expression and cancer classification (5 papers). Yingtao Bi collaborates with scholars based in United States, China and Ireland. Yingtao Bi's co-authors include Ramana V. Davuluri, Sharmistha Pal, Donald M. O’Rourke, María Martínez-Lage, Nadia Dahmane, Luke Macyszyn, Chenqi Hu, Liang Jin, Yu Tian and Julia Tchou and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Yingtao Bi

39 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yingtao Bi United States 20 626 260 211 206 203 41 1.3k
Friedrich Feuerhake Germany 21 433 0.7× 389 1.5× 395 1.9× 133 0.6× 204 1.0× 89 1.6k
Finbarr O’Sullivan Ireland 17 388 0.6× 152 0.6× 229 1.1× 374 1.8× 204 1.0× 55 1.1k
Michael Bockmayr Germany 21 394 0.6× 132 0.5× 649 3.1× 170 0.8× 278 1.4× 35 1.4k
Panu E. Kovanen Finland 26 627 1.0× 288 1.1× 691 3.3× 415 2.0× 237 1.2× 44 2.3k
Dorina Gui United States 23 862 1.4× 191 0.7× 345 1.6× 92 0.4× 243 1.2× 52 1.7k
Aibin Liang China 19 689 1.1× 247 0.9× 498 2.4× 65 0.3× 182 0.9× 117 1.5k
Alexander Bagaev United States 11 508 0.8× 227 0.9× 779 3.7× 86 0.4× 327 1.6× 32 1.5k
Lukas P. Frenzel Germany 19 664 1.1× 299 1.1× 354 1.7× 77 0.4× 225 1.1× 34 1.3k
Delphine Loussouarn France 28 976 1.6× 337 1.3× 694 3.3× 122 0.6× 574 2.8× 76 2.3k
Qianghu Wang China 22 1.1k 1.8× 407 1.6× 406 1.9× 65 0.3× 649 3.2× 59 2.1k

Countries citing papers authored by Yingtao Bi

Since Specialization
Citations

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

Fields of papers citing papers by Yingtao Bi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yingtao Bi

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

All Works

20 of 20 papers shown
1.
2.
Jin, Liang, Michael Macoritto, Yingtao Bi, et al.. (2024). Multi-Omics Characterization of Colon Mucosa and Submucosa/Wall from Crohn’s Disease Patients. International Journal of Molecular Sciences. 25(10). 5108–5108.
3.
Ravishankar, B, Preeti Lal, Thierry Sornasse, et al.. (2023). POS1545 MODULATION OF SERUM BIOMARKERS IN PATIENTS WITH PSA TREATED WITH RISANKIZUMAB IN THE PHASE 3 KEEPSAKE 2 STUDY. 1141–1142. 1 indexed citations
4.
5.
Chen, Wanqiu, Yongmei Zhao, Xin Chen, et al.. (2020). A multicenter study benchmarking single-cell RNA sequencing technologies using reference samples. Nature Biotechnology. 39(9). 1103–1114. 61 indexed citations
6.
Mashiko, Shunya, Rebecca M. Edelmayer, Yingtao Bi, et al.. (2019). Persistence of Inflammatory Phenotype in Residual Psoriatic Plaques in Patients on Effective Biologic Therapy. Journal of Investigative Dermatology. 140(5). 1015–1025.e4. 13 indexed citations
7.
Martínez-Lage, María, Timothy M. Lynch, Yingtao Bi, et al.. (2019). Immune landscapes associated with different glioblastoma molecular subtypes. Acta Neuropathologica Communications. 7(1). 203–203. 138 indexed citations
8.
Paunesku, Tatjana, Koshonna Brown, Sumita Raha, et al.. (2019). Protein Binding Effects of Dopamine Coated Titanium Dioxide Shell Nanoparticles. SHILAP Revista de lepidopterología. 2(4). 393–438. 5 indexed citations
9.
Hamvas, Aaron, Rui Feng, Yingtao Bi, et al.. (2018). Exome sequencing identifies gene variants and networks associated with extreme respiratory outcomes following preterm birth. BMC Genetics. 19(1). 94–94. 25 indexed citations
10.
Malchenko, Sergey, Simone Treiger Sredni, Jerusha Boyineni, et al.. (2018). Characterization of brain tumor initiating cells isolated from an animal model of CNS primitive neuroectodermal tumors. Oncotarget. 9(17). 13733–13747. 9 indexed citations
11.
Wang, Yiyang, Xianpeng Liu, Li Zhou, et al.. (2017). Identifying the ubiquitination targets of E6AP by orthogonal ubiquitin transfer. Nature Communications. 8(1). 2232–2232. 39 indexed citations
12.
Malchenko, Sergey, Simone Treiger Sredni, Yingtao Bi, et al.. (2017). Stabilization of HIF-1α and HIF-2α, up-regulation of MYCC and accumulation of stabilized p53 constitute hallmarks of CNS-PNET animal model. PLoS ONE. 12(3). e0173106–e0173106. 4 indexed citations
13.
Bi, Yingtao, et al.. (2016). An innovative two-stage fuzzy kNN-DST classifier for unknown intrusion detection. The International Arab Journal of Information Technology. 13(4). 359–366. 4 indexed citations
14.
Bell, Jonathan B., Frank Eckerdt, Yingtao Bi, et al.. (2016). MNK Inhibition Disrupts Mesenchymal Glioma Stem Cells and Prolongs Survival in a Mouse Model of Glioblastoma. Molecular Cancer Research. 14(10). 984–993. 30 indexed citations
15.
Dapas, Matthew, Manoj Kandpal, Yingtao Bi, & Ramana V. Davuluri. (2016). Comparative evaluation of isoform-level gene expression estimation algorithms for RNA-seq and exon-array platforms. Briefings in Bioinformatics. 18(2). bbw016–bbw016. 20 indexed citations
16.
Walsh, Alice M., Gurpreet S. Kapoor, Janine M. Buonato, et al.. (2015). Sprouty2 Drives Drug Resistance and Proliferation in Glioblastoma. Molecular Cancer Research. 13(8). 1227–1237. 24 indexed citations
17.
Pisapia, Jared, Luke Macyszyn, Hamed Akbari, et al.. (2015). 135 Imaging Patterns Predict Patient Survival and Molecular Subtype in Glioblastoma Using Machine Learning Techniques. Neurosurgery. 62(Supplement 1). 209–209. 2 indexed citations
18.
Zhang, Zhongfa, Sharmistha Pal, Yingtao Bi, Julia Tchou, & Ramana V. Davuluri. (2013). Isoform level expression profiles provide better cancer signatures than gene level expression profiles. Genome Medicine. 5(4). 33–33. 36 indexed citations
19.
Bi, Yingtao, Hyunsoo Kim, Ravi Gupta, & Ramana V. Davuluri. (2011). Tree-Based Position Weight Matrix Approach to Model Transcription Factor Binding Site Profiles. PLoS ONE. 6(9). e24210–e24210. 18 indexed citations
20.
Bi, Yingtao & Daniel R. Jeske. (2010). The efficiency of logistic regression compared to normal discriminant analysis under class-conditional classification noise. Journal of Multivariate Analysis. 101(7). 1622–1637. 19 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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