Nora Sánchez

3.3k total citations
19 papers, 498 citations indexed

About

Nora Sánchez is a scholar working on Molecular Biology, Cancer Research and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Nora Sánchez has authored 19 papers receiving a total of 498 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 10 papers in Cancer Research and 4 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Nora Sánchez's work include Cancer Genomics and Diagnostics (10 papers), Bioinformatics and Genomic Networks (4 papers) and Lung Cancer Treatments and Mutations (4 papers). Nora Sánchez is often cited by papers focused on Cancer Genomics and Diagnostics (10 papers), Bioinformatics and Genomic Networks (4 papers) and Lung Cancer Treatments and Mutations (4 papers). Nora Sánchez collaborates with scholars based in United States, Mexico and Nicaragua. Nora Sánchez's co-authors include Joey V. Barnett, Funda Meric‐Bernstam, Kenna Shaw, Gordon B. Mills, Vijaykumar Holla, Yekaterina B. Khotskaya, Jia Zeng, Ann M. Bailey, Beate C. Litzenburger and Md Abu Shufean and has published in prestigious journals such as Journal of Clinical Oncology, Cancer and Cancer Research.

In The Last Decade

Nora Sánchez

19 papers receiving 489 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nora Sánchez United States 13 261 187 140 139 73 19 498
Reinaldo Chacón Argentina 13 166 0.6× 151 0.8× 92 0.7× 302 2.2× 59 0.8× 26 580
Wen Wei China 13 166 0.6× 202 1.1× 111 0.8× 262 1.9× 65 0.9× 21 551
Dalin Li China 15 210 0.8× 130 0.7× 110 0.8× 296 2.1× 62 0.8× 27 650
Pablo Berlanga France 12 186 0.7× 97 0.5× 167 1.2× 181 1.3× 49 0.7× 54 492
Fernanda I. Arnaldez United States 11 202 0.8× 84 0.4× 110 0.8× 196 1.4× 38 0.5× 20 513
Yassamin Feroz Zada Canada 10 190 0.7× 101 0.5× 46 0.3× 80 0.6× 52 0.7× 17 680
Bilge Aktaş Türkiye 9 268 1.0× 186 1.0× 72 0.5× 155 1.1× 42 0.6× 20 505
Daniel A. Weiser United States 11 259 1.0× 185 1.0× 144 1.0× 161 1.2× 32 0.4× 35 529
Johannes Fritzmann Germany 13 392 1.5× 154 0.8× 78 0.6× 218 1.6× 59 0.8× 33 667

Countries citing papers authored by Nora Sánchez

Since Specialization
Citations

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

Fields of papers citing papers by Nora Sánchez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nora Sánchez

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

All Works

19 of 19 papers shown
1.
Pilié, Patrick G., Khalida Wani, Nora Sánchez, et al.. (2020). Identifying functional loss of ATM gene in patients with advanced cancer.. Journal of Clinical Oncology. 38(15_suppl). 3629–3629. 1 indexed citations
2.
Hess, Kenneth R., Filip Jankú, Nora Sánchez, et al.. (2019). Cell-free Circulating Tumor DNA Variant Allele Frequency Associates with Survival in Metastatic Cancer. Clinical Cancer Research. 26(8). 1924–1931. 40 indexed citations
3.
Johnson, Amber M., Jia Zeng, Vijaykumar Holla, et al.. (2019). Rapamycin − mTOR + BRAF = ? Using relational similarity to find therapeutically relevant drug-gene relationships in unstructured text. Journal of Biomedical Informatics. 90. 103094–103094. 3 indexed citations
4.
Sánchez, Nora, Michael Kahle, Ann M. Bailey, et al.. (2019). Identification of Actionable Genomic Alterations Using Circulating Cell-Free DNA. JCO Precision Oncology. 3(3). 1–10. 8 indexed citations
5.
Zeng, Jia, Md Abu Shufean, Yekaterina B. Khotskaya, et al.. (2019). OCTANE: Oncology Clinical Trial Annotation Engine. JCO Clinical Cancer Informatics. 3(3). 1–11. 17 indexed citations
6.
Kurnit, Katherine C., Ecaterina E. Dumbrava, Beate C. Litzenburger, et al.. (2018). Precision Oncology Decision Support: Current Approaches and Strategies for the Future. Clinical Cancer Research. 24(12). 2719–2731. 41 indexed citations
7.
Lam, Michael, Allan Andresson Lima Pereira, Jonathan M. Loree, et al.. (2018). Effect of matched therapy in metastatic colorectal cancer on progression free survival in the phase I setting.. Journal of Clinical Oncology. 36(15_suppl). 3522–3522. 1 indexed citations
8.
Kurnit, Katherine C., Ann M. Bailey, Jia Zeng, et al.. (2017). “Personalized Cancer Therapy”: A Publicly Available Precision Oncology Resource. Cancer Research. 77(21). e123–e126. 29 indexed citations
9.
Holla, Vijaykumar, Yasir Y. Elamin, Ann M. Bailey, et al.. (2017). ALK: a tyrosine kinase target for cancer therapy. Molecular Case Studies. 3(1). a001115–a001115. 128 indexed citations
10.
Johnson, Amber M., Yekaterina B. Khotskaya, Lauren Brusco, et al.. (2017). Clinical Use of Precision Oncology Decision Support. JCO Precision Oncology. 2017(1). 1–12. 24 indexed citations
11.
Brusco, Lauren, Chetna Wathoo, Kenna Shaw, et al.. (2017). Physician interpretation of genomic test results and treatment selection. Cancer. 124(5). 966–972. 10 indexed citations
12.
Sánchez, Nora, Gordon B. Mills, & Kenna Shaw. (2017). Precision Oncology: Neither a Silver Bullet nor a Dream. Pharmacogenomics. 18(16). 1525–1539. 12 indexed citations
13.
Sánchez, Nora, Todd A. Townsend, W. David Merryman, et al.. (2016). Common pathways regulate Type III TGFβ receptor-dependent cell invasion in epicardial and endocardial cells. Cellular Signalling. 28(6). 688–698. 17 indexed citations
14.
Johnson, Amber M., Jia Zeng, Alejandro Araya, et al.. (2016). Automated identification of molecular effects of drugs (AIMED). Journal of the American Medical Informatics Association. 23(4). 758–765. 17 indexed citations
15.
Maldonado, Carolina Solís, et al.. (2013). Nicaraguan Surgical and Anesthesia Infrastructure: Survey of Ministry of Health Hospitals. World Journal of Surgery. 37(9). 2109–2121. 21 indexed citations
16.
Hill, Cynthia R., Nora Sánchez, Joseph D. Love, et al.. (2012). BMP2 signals loss of epithelial character in epicardial cells but requires the Type III TGFβ receptor to promote invasion. Cellular Signalling. 24(5). 1012–1022. 38 indexed citations
17.
Sánchez, Nora & Joey V. Barnett. (2011). TGFβ and BMP-2 regulate epicardial cell invasion via TGFβR3 activation of the Par6/Smurf1/RhoA pathway. Cellular Signalling. 24(2). 539–548. 50 indexed citations
18.
Sánchez, Nora, Cynthia R. Hill, Joseph D. Love, et al.. (2011). The cytoplasmic domain of TGFβR3 through its interaction with the scaffolding protein, GIPC, directs epicardial cell behavior. Developmental Biology. 358(2). 331–343. 28 indexed citations
19.
Ray, Sanhita, Fu‐Hua Xu, Ping Li, et al.. (2007). Increased Level of Cellular Bip Critically Determines Estrogenic Potency for a Xenoestrogen Kepone in the Mouse Uterus. Endocrinology. 148(10). 4774–4785. 13 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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