Candida Manelfi

770 total citations
19 papers, 293 citations indexed

About

Candida Manelfi is a scholar working on Molecular Biology, Computational Theory and Mathematics and Infectious Diseases. According to data from OpenAlex, Candida Manelfi has authored 19 papers receiving a total of 293 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 11 papers in Computational Theory and Mathematics and 7 papers in Infectious Diseases. Recurrent topics in Candida Manelfi's work include Computational Drug Discovery Methods (11 papers), SARS-CoV-2 and COVID-19 Research (7 papers) and Protein Structure and Dynamics (3 papers). Candida Manelfi is often cited by papers focused on Computational Drug Discovery Methods (11 papers), SARS-CoV-2 and COVID-19 Research (7 papers) and Protein Structure and Dynamics (3 papers). Candida Manelfi collaborates with scholars based in Italy, Germany and Sweden. Candida Manelfi's co-authors include Andrea R. Beccari, Carmine Talarico, Alessandro Pedretti, Silvia Gervasoni, Giulio Vistoli, Carmen Cerchia, Erik Lindahl, Philip Gribbon, Andrea Zaliani and Marica Gemei and has published in prestigious journals such as Bioinformatics, Scientific Reports and International Journal of Molecular Sciences.

In The Last Decade

Candida Manelfi

19 papers receiving 288 citations

Peers

Candida Manelfi
Zina Itkin United States
Suyash Pant India
Lovika Mittal India
Carmine Talarico Italy
Anchala Kumari India
Juliana C. Ferreira United Arab Emirates
Li Liang China
Daniel Korn United States
Min‐Feng Hsu Taiwan
Pengjiao Hou China
Zina Itkin United States
Candida Manelfi
Citations per year, relative to Candida Manelfi Candida Manelfi (= 1×) peers Zina Itkin

Countries citing papers authored by Candida Manelfi

Since Specialization
Citations

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

Fields of papers citing papers by Candida Manelfi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Candida Manelfi

This figure shows the co-authorship network connecting the top 25 collaborators of Candida Manelfi. A scholar is included among the top collaborators of Candida Manelfi 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 Candida Manelfi. Candida Manelfi 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.
Manelfi, Candida, Valerio Tazzari, Filippo Lunghini, et al.. (2024). “DompeKeys”: a set of novel substructure-based descriptors for efficient chemical space mapping, development and structural interpretation of machine learning models, and indexing of large databases. Journal of Cheminformatics. 16(1). 21–21. 1 indexed citations
2.
Kuzikov, Maria, Jeanette Reinshagen, Angela Corona, et al.. (2024). Drug repurposing screen to identify inhibitors of the RNA polymerase (nsp12) and helicase (nsp13) from SARS-CoV-2 replication and transcription complex. Virus Research. 343. 199356–199356. 8 indexed citations
3.
Corona, Angela, Valentina Noemi Madia, Riccardo De Santis, et al.. (2023). Diketo acid inhibitors of nsp13 of SARS-CoV-2 block viral replication. Antiviral Research. 217. 105697–105697. 7 indexed citations
4.
Iaconis, Daniela, Francesca Caccuri, Candida Manelfi, et al.. (2023). DHFR Inhibitors Display a Pleiotropic Anti-Viral Activity against SARS-CoV-2: Insights into the Mechanisms of Action. Viruses. 15(5). 1128–1128. 2 indexed citations
5.
Gervasoni, Silvia, Candida Manelfi, Carmine Talarico, et al.. (2023). Target Prediction by Multiple Virtual Screenings: Analyzing the SARS-CoV-2 Phenotypic Screening by the Docking Simulations Submitted to the MEDIATE Initiative. International Journal of Molecular Sciences. 25(1). 450–450. 2 indexed citations
6.
Vittorio, Serena, Candida Manelfi, Silvia Gervasoni, et al.. (2022). Computational Insights into the Sequence-Activity Relationships of the NGF(1–14) Peptide by Molecular Dynamics Simulations. Cells. 11(18). 2808–2808. 6 indexed citations
7.
Gervasoni, Silvia, Carmine Talarico, Candida Manelfi, et al.. (2022). Extensive Sampling of Molecular Dynamics Simulations to Identify Reliable Protein Structures for Optimized Virtual Screening Studies: The Case of the hTRPM8 Channel. International Journal of Molecular Sciences. 23(14). 7558–7558. 2 indexed citations
8.
Gadioli, Davide, Candida Manelfi, Carmine Talarico, et al.. (2022). An extreme-scale virtual screening platform for drug discovery. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 211–212. 3 indexed citations
9.
Gadioli, Davide, Candida Manelfi, Carmine Talarico, et al.. (2022). EXSCALATE: An Extreme-Scale Virtual Screening Platform for Drug Discovery Targeting Polypharmacology to Fight SARS-CoV-2. IEEE Transactions on Emerging Topics in Computing. 11(1). 170–181. 12 indexed citations
10.
Corona, Angela, Carmine Talarico, Candida Manelfi, et al.. (2022). Natural Compounds Inhibit SARS-CoV-2 nsp13 Unwinding and ATPase Enzyme Activities. ACS Pharmacology & Translational Science. 5(4). 226–239. 51 indexed citations
11.
Albani, Simone, Maria Kuzikov, Elisa Costanzi, et al.. (2021). A Blueprint for High Affinity SARS-CoV-2 Mpro Inhibitors from Activity-Based Compound Library Screening Guided by Analysis of Protein Dynamics. ACS Pharmacology & Translational Science. 4(3). 1079–1095. 35 indexed citations
12.
Manelfi, Candida, Silvia Gervasoni, Carmine Talarico, et al.. (2021). Combining Different Docking Engines and Consensus Strategies to Design and Validate Optimized Virtual Screening Protocols for the SARS-CoV-2 3CL Protease. Molecules. 26(4). 797–797. 14 indexed citations
13.
Manelfi, Candida, Marica Gemei, Carmine Talarico, et al.. (2021). “Molecular Anatomy”: a new multi-dimensional hierarchical scaffold analysis tool. Journal of Cheminformatics. 13(1). 54–54. 15 indexed citations
14.
Gervasoni, Silvia, Giulio Vistoli, Carmine Talarico, et al.. (2020). A Comprehensive Mapping of the Druggable Cavities within the SARS-CoV-2 Therapeutically Relevant Proteins by Combining Pocket and Docking Searches as Implemented in Pockets 2.0. International Journal of Molecular Sciences. 21(14). 5152–5152. 25 indexed citations
15.
Grottesi, Alessandro, Neva Bešker, Andrew Emerson, et al.. (2020). Computational Studies of SARS-CoV-2 3CLpro: Insights from MD Simulations. International Journal of Molecular Sciences. 21(15). 5346–5346. 45 indexed citations
16.
Gemei, Marica, Carmine Talarico, Laura Brandolini, et al.. (2020). Binding Mode Exploration of B1 Receptor Antagonists’ by the Use of Molecular Dynamics and Docking Simulation—How Different Target Engagement Can Determine Different Biological Effects. International Journal of Molecular Sciences. 21(20). 7677–7677. 2 indexed citations
17.
Talarico, Carmine, Silvia Gervasoni, Candida Manelfi, et al.. (2020). Combining Molecular Dynamics and Docking Simulations to Develop Targeted Protocols for Performing Optimized Virtual Screening Campaigns on the hTRPM8 Channel. International Journal of Molecular Sciences. 21(7). 2265–2265. 20 indexed citations
18.
Papoff, Giuliana, Dario Presutti, Giulia Bolasco, et al.. (2018). CASP4 gene silencing in epithelial cancer cells leads to impairment of cell migration, cell-matrix adhesion and tissue invasion. Scientific Reports. 8(1). 17705–17705. 24 indexed citations
19.
Monte, Matteo Lo, Candida Manelfi, Marica Gemei, Daniela Corda, & Andrea R. Beccari. (2018). ADPredict: ADP-ribosylation site prediction based on physicochemical and structural descriptors. Bioinformatics. 34(15). 2566–2574. 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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