Ada Sedova

648 total citations
26 papers, 196 citations indexed

About

Ada Sedova is a scholar working on Molecular Biology, Computational Theory and Mathematics and Materials Chemistry. According to data from OpenAlex, Ada Sedova has authored 26 papers receiving a total of 196 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 7 papers in Computational Theory and Mathematics and 6 papers in Materials Chemistry. Recurrent topics in Ada Sedova's work include Protein Structure and Dynamics (6 papers), Computational Drug Discovery Methods (6 papers) and Machine Learning in Materials Science (4 papers). Ada Sedova is often cited by papers focused on Protein Structure and Dynamics (6 papers), Computational Drug Discovery Methods (6 papers) and Machine Learning in Materials Science (4 papers). Ada Sedova collaborates with scholars based in United States, Germany and Switzerland. Ada Sedova's co-authors include Jens Gläser, Jeremy C. Smith, Gerd‐Uwe Flechsig, Matthew Baker, Josh V. Vermaas, Swen Boehm, David Rogers, Óscar Hernández, Wael Elwasif and Jeff Larkin and has published in prestigious journals such as Bioinformatics, Biochemistry and ACS Applied Materials & Interfaces.

In The Last Decade

Ada Sedova

24 papers receiving 193 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ada Sedova United States 8 105 67 44 25 21 26 196
Paul S. Bond United Kingdom 8 106 1.0× 25 0.4× 45 1.0× 15 0.6× 15 0.7× 13 201
Iain Bethune United Kingdom 6 49 0.5× 30 0.4× 23 0.5× 19 0.8× 20 1.0× 24 167
Xinxin Liu China 7 38 0.4× 129 1.9× 33 0.8× 58 2.3× 15 0.7× 13 249
Pietro Bongini Italy 8 72 0.7× 100 1.5× 54 1.2× 13 0.5× 9 0.4× 21 255
Austin Clyde United States 7 74 0.7× 75 1.1× 32 0.7× 11 0.4× 7 0.3× 11 149
Douglas J. Ierardi United States 5 128 1.2× 16 0.2× 24 0.5× 14 0.6× 16 0.8× 9 201
Özlem Özmen Garibay United States 6 86 0.8× 85 1.3× 30 0.7× 7 0.3× 8 0.4× 26 187
Swen Boehm United States 6 34 0.3× 41 0.6× 19 0.4× 7 0.3× 78 3.7× 9 147
Manish K. Gupta India 10 118 1.1× 26 0.4× 22 0.5× 26 1.0× 74 3.5× 44 294
Hieu Dinh United States 10 177 1.7× 8 0.1× 73 1.7× 15 0.6× 35 1.7× 20 348

Countries citing papers authored by Ada Sedova

Since Specialization
Citations

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

Fields of papers citing papers by Ada Sedova

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ada Sedova

This figure shows the co-authorship network connecting the top 25 collaborators of Ada Sedova. A scholar is included among the top collaborators of Ada Sedova 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 Ada Sedova. Ada Sedova 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.
Manard, Benjamin T., Lyndsey Hendriks, Amber N. Bible, et al.. (2024). Quantifying platinum binding on protein-functionalized magnetic microparticles using single particle-ICP-TOF-MS. Analytical Methods. 16(20). 3192–3201. 4 indexed citations
2.
Kearney, Logan T., et al.. (2024). Deep-Learning Interatomic Potential Connects Molecular Structural Ordering to the Macroscale Properties of Polyacrylonitrile. ACS Applied Materials & Interfaces. 16(28). 36878–36891. 7 indexed citations
3.
Roy, Santanu, et al.. (2024). Tracing mechanistic pathways and reaction kinetics toward equilibrium in reactive molten salts. Chemical Science. 15(9). 3116–3129. 3 indexed citations
4.
5.
Morehead, Alex, Chen Chen, Ada Sedova, & Jianlin Cheng. (2023). DIPS-Plus: The enhanced database of interacting protein structures for interface prediction. Scientific Data. 10(1). 509–509. 10 indexed citations
6.
Sedova, Ada, et al.. (2023). Multiobjective Hyperparameter Optimization for Deep Learning Interatomic Potential Training Using NSGA-II. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 172–179. 3 indexed citations
7.
Gao, Mu, Bryan Piatkowski, Avinash Sreedasyam, et al.. (2023). Predicted structural proteome of Sphagnum divinum and proteome-scale annotation. Bioinformatics. 39(8). 2 indexed citations
8.
Rogers, David, Rupesh Agarwal, Josh V. Vermaas, et al.. (2023). SARS-CoV2 billion-compound docking. Scientific Data. 10(1). 173–173. 14 indexed citations
9.
Sedova, Ada, et al.. (2023). tinyIFD: A High-Throughput Binding Pose Refinement Workflow Through Induced-Fit Ligand Docking. Journal of Chemical Information and Modeling. 63(11). 3438–3447. 7 indexed citations
10.
Gläser, Jens, Ada Sedova, Stephanie Galanie, et al.. (2022). Hit Expansion of a Noncovalent SARS-CoV-2 Main Protease Inhibitor. ACS Pharmacology & Translational Science. 5(4). 255–265. 18 indexed citations
11.
Elwasif, Wael, et al.. (2022). Portability for GPU-accelerated molecular docking applications for cloud and HPC: can portable compiler directives provide performance across all platforms?. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 975–984. 6 indexed citations
12.
Gao, Mu, Alex Morehead, Chen Chen, et al.. (2021). High-Performance Deep Learning Toolbox for Genome-Scale Prediction of Protein Structure and Function. PubMed. 2021. 46–57. 6 indexed citations
13.
Hernández, Óscar, et al.. (2021). Addressing Load Imbalance in Bioinformatics and Biomedical Applications: Efficient Scheduling across Multiple GPUs. 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). 1992–1999. 3 indexed citations
14.
Scheinberg, Aaron, et al.. (2020). Performance Portability of Molecular Docking Miniapp On Leadership Computing Platforms. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 36–44. 6 indexed citations
15.
Vermaas, Josh V., Ada Sedova, Matthew Baker, et al.. (2020). Supercomputing Pipelines Search for Therapeutics Against COVID-19. Computing in Science & Engineering. 23(1). 7–16. 22 indexed citations
16.
Sedova, Ada, et al.. (2018). High-Performance Molecular Dynamics Simulation for Biological and Materials Sciences: Challenges of Performance Portability. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1–13. 14 indexed citations
17.
Pandey, Anup, Ada Sedova, Luke L. Daemen, Yongqiang Cheng, & Anibal J. Ramirez‐Cuesta. (2018). Exposing Key Vibrational Contributions to Properties of Organic Molecular Solids with High Signal, Low Frequency Neutron Spectroscopy and Ab Initio Simulations. Crystal Growth & Design. 18(9). 4815–4821. 5 indexed citations
18.
Sedova, Ada, et al.. (2016). The Osmium Tetroxide Bipyridine‐labeled DNA Probe: Hairpin Conformations and Characterization of Redox‐label Behavior. Electroanalysis. 29(1). 51–59. 3 indexed citations
19.
20.
Sedova, Ada & Nilesh K. Banavali. (2015). RNA approaches the B‐form in stacked single strand dinucleotide contexts. Biopolymers. 105(2). 65–82. 5 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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