Iván Cornella‐Taracido

2.1k total citations
20 papers, 714 citations indexed

About

Iván Cornella‐Taracido is a scholar working on Molecular Biology, Organic Chemistry and Cellular and Molecular Neuroscience. According to data from OpenAlex, Iván Cornella‐Taracido has authored 20 papers receiving a total of 714 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 4 papers in Organic Chemistry and 3 papers in Cellular and Molecular Neuroscience. Recurrent topics in Iván Cornella‐Taracido's work include Computational Drug Discovery Methods (3 papers), Ubiquitin and proteasome pathways (3 papers) and Chemical Synthesis and Analysis (2 papers). Iván Cornella‐Taracido is often cited by papers focused on Computational Drug Discovery Methods (3 papers), Ubiquitin and proteasome pathways (3 papers) and Chemical Synthesis and Analysis (2 papers). Iván Cornella‐Taracido collaborates with scholars based in United States, Switzerland and Spain. Iván Cornella‐Taracido's co-authors include T. Ross Kelly, John A. Tallarico, Adam G. Schwaid, Markus Schirle, Simon M. Bushell, David J. Schwalb, Eugene C. Petrella, Jason Murphy, An Chi and Yajun Zhao and has published in prestigious journals such as Journal of the American Chemical Society, Blood and Scientific Reports.

In The Last Decade

Iván Cornella‐Taracido

20 papers receiving 702 citations

Peers

Iván Cornella‐Taracido
Rahul S. Kathayat United States
Νicholas Barlow Australia
Jaimeen D. Majmudar United States
Mark A. Jarosinski United States
Ana Negri Spain
Gildon Choi South Korea
Andy Merritt United Kingdom
Julie E. Penzotti United States
K. Ulrich Wendt Germany
Nicole D. Barth United Kingdom
Rahul S. Kathayat United States
Iván Cornella‐Taracido
Citations per year, relative to Iván Cornella‐Taracido Iván Cornella‐Taracido (= 1×) peers Rahul S. Kathayat

Countries citing papers authored by Iván Cornella‐Taracido

Since Specialization
Citations

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

Fields of papers citing papers by Iván Cornella‐Taracido

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Iván Cornella‐Taracido. 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 Iván Cornella‐Taracido. The network helps show where Iván Cornella‐Taracido may publish in the future.

Co-authorship network of co-authors of Iván Cornella‐Taracido

This figure shows the co-authorship network connecting the top 25 collaborators of Iván Cornella‐Taracido. A scholar is included among the top collaborators of Iván Cornella‐Taracido 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 Iván Cornella‐Taracido. Iván Cornella‐Taracido 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.
Ruprecht, Benjamin, Wei Lan, Li Zheng, et al.. (2022). Chemoproteomic profiling to identify activity changes and functional inhibitors of DNA-binding proteins. Cell chemical biology. 29(11). 1639–1648.e4. 8 indexed citations
2.
Mortison, Jonathan D., et al.. (2021). Rapid Evaluation of Small Molecule Cellular Target Engagement with a Luminescent Thermal Shift Assay. ACS Medicinal Chemistry Letters. 12(8). 1288–1294. 23 indexed citations
3.
Ruprecht, Benjamin, Julie Di Bernardo, Zhao Wang, et al.. (2020). A mass spectrometry-based proteome map of drug action in lung cancer cell lines. Nature Chemical Biology. 16(10). 1111–1119. 34 indexed citations
4.
Cornella‐Taracido, Iván & Carlos Garcı́a-Echeverrı́a. (2020). Monovalent protein-degraders – Insights and future perspectives. Bioorganic & Medicinal Chemistry Letters. 30(12). 127202–127202. 13 indexed citations
5.
Lam, Pui‐Ying, Peter S. Kutchukian, Rajan Anand, et al.. (2020). Cyp1 Inhibition Prevents Doxorubicin‐Induced Cardiomyopathy in a Zebrafish Heart‐Failure Model. ChemBioChem. 21(13). 1905–1910. 20 indexed citations
6.
Schwaid, Adam G., et al.. (2018). Comparison of the Rat and Human Dorsal Root Ganglion Proteome. Scientific Reports. 8(1). 13469–13469. 31 indexed citations
7.
Asnani, Aarti, Yan Liu, You Wang, et al.. (2018). Highly potent visnagin derivatives inhibit Cyp1 and prevent doxorubicin cardiotoxicity. JCI Insight. 3(1). 33 indexed citations
8.
Casás‐Selves, Matias, Andrew X. Zhang, James J. Dowling, et al.. (2017). Target Deconvolution Efforts on Wnt Pathway Screen Reveal Dual Modulation of Oxidative Phosphorylation and SERCA2. ChemMedChem. 12(12). 917–924. 1 indexed citations
9.
Schwaid, Adam G. & Iván Cornella‐Taracido. (2017). Causes and Significance of Increased Compound Potency in Cellular or Physiological Contexts. Journal of Medicinal Chemistry. 61(5). 1767–1773. 19 indexed citations
10.
Honda, Ayako, Edmund Harrington, Iván Cornella‐Taracido, et al.. (2015). Potent, Selective, and Orally Bioavailable Inhibitors of VPS34 Provide Chemical Tools to Modulate Autophagy in Vivo. ACS Medicinal Chemistry Letters. 7(1). 72–76. 40 indexed citations
11.
Thomas, Jason R., Edmund Harrington, Jason Murphy, et al.. (2015). Conversion of a Single Polypharmacological Agent into Selective Bivalent Inhibitors of Intracellular Kinase Activity. ACS Chemical Biology. 11(1). 121–131. 18 indexed citations
12.
Burgett, Anthony W. G., Thomas B. Poulsen, Kittikhun Wangkanont, et al.. (2011). Natural products reveal cancer cell dependence on oxysterol-binding proteins. Nature Chemical Biology. 7(9). 639–647. 208 indexed citations
13.
Schirle, Markus, Eugene C. Petrella, Scott M. Brittain, et al.. (2011). Kinase Inhibitor Profiling Using Chemoproteomics. Methods in molecular biology. 795. 161–177. 12 indexed citations
14.
Russo, Carla, Iván Cornella‐Taracido, Luisa Galli‐Stampino, et al.. (2011). Small molecule Toll-like receptor 7 agonists localize to the MHC class II loading compartment of human plasmacytoid dendritic cells. Blood. 117(21). 5683–5691. 30 indexed citations
15.
Bender, Andreas, Д. А. Михайлов, Meir Glick, et al.. (2009). Use of Ligand Based Models for Protein Domains To Predict Novel Molecular Targets and Applications To Triage Affinity Chromatography Data. Journal of Proteome Research. 8(5). 2575–2585. 17 indexed citations
16.
Kelly, T. Ross, Xiaolu Cai, Fehmi Damkaci, et al.. (2006). Progress toward a Rationally Designed, Chemically Powered Rotary Molecular Motor. Journal of the American Chemical Society. 129(2). 376–386. 149 indexed citations
17.
Cornella‐Taracido, Iván, et al.. (2004). Stereoselective convergent synthesis of 24-substituted metabolites and analogues of vitamin D. The Journal of Steroid Biochemistry and Molecular Biology. 89-90(1-5). 19–23. 9 indexed citations
18.
Cornella‐Taracido, Iván & T. Ross Kelly. (2004). Synthesis of Porritoxin. The Journal of Organic Chemistry. 69(6). 2191–2193. 14 indexed citations
19.
Sestelo, José Pérez, et al.. (2002). Stereoselective Convergent Synthesis of 24,25-Dihydroxyvitamin D3 Metabolites: A Practical Approach. Chemistry - A European Journal. 8(12). 2747–2747. 13 indexed citations
20.
Cornella‐Taracido, Iván, José Pérez Sestelo, Antonio Mouriño, & Luis A. Sarandeses. (2002). Synthesis of New 18-Substituted Analogues of Calcitriol Using a Photochemical Remote Functionalization. The Journal of Organic Chemistry. 67(14). 4707–4714. 22 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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