Aybar C. Acar

534 total citations
20 papers, 297 citations indexed

About

Aybar C. Acar is a scholar working on Molecular Biology, Computational Theory and Mathematics and Artificial Intelligence. According to data from OpenAlex, Aybar C. Acar has authored 20 papers receiving a total of 297 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 5 papers in Computational Theory and Mathematics and 4 papers in Artificial Intelligence. Recurrent topics in Aybar C. Acar's work include Computational Drug Discovery Methods (5 papers), Machine Learning in Bioinformatics (3 papers) and Protein Structure and Dynamics (3 papers). Aybar C. Acar is often cited by papers focused on Computational Drug Discovery Methods (5 papers), Machine Learning in Bioinformatics (3 papers) and Protein Structure and Dynamics (3 papers). Aybar C. Acar collaborates with scholars based in Türkiye, United States and Germany. Aybar C. Acar's co-authors include Tunca Doğan, Kemal Turhan, Heval Ataş, Amihai Motro, Gökhan Karakülah, Özlen Konu, Cengiz Yakıcıer, Volkan Atalay, Rengül Çetin-Atalay and Koray Dogan Kaya and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and International Journal of Molecular Sciences.

In The Last Decade

Aybar C. Acar

19 papers receiving 287 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Aybar C. Acar Türkiye 8 154 50 48 29 28 20 297
Yuzhou Chen United States 10 69 0.4× 29 0.6× 30 0.6× 29 1.0× 18 0.6× 52 381
Hongwei Huang China 11 128 0.8× 30 0.6× 112 2.3× 51 1.8× 8 0.3× 20 384
Xianjun Shen China 10 170 1.1× 78 1.6× 62 1.3× 40 1.4× 6 0.2× 54 304
Aanchal Mongia India 9 235 1.5× 60 1.2× 49 1.0× 28 1.0× 7 0.3× 17 339
Achille Zappa Ireland 7 106 0.7× 14 0.3× 76 1.6× 25 0.9× 5 0.2× 14 277
Tapas Bhadra India 10 150 1.0× 36 0.7× 139 2.9× 80 2.8× 14 0.5× 21 339
Mohamed Elati France 11 197 1.3× 20 0.4× 42 0.9× 15 0.5× 6 0.2× 35 320
Roozbeh Dehghannasiri United States 10 130 0.8× 46 0.9× 99 2.1× 13 0.4× 15 0.5× 26 319
Wiesław Paja Poland 9 60 0.4× 26 0.5× 62 1.3× 12 0.4× 37 1.3× 55 354

Countries citing papers authored by Aybar C. Acar

Since Specialization
Citations

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

Fields of papers citing papers by Aybar C. Acar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Aybar C. Acar. 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 Aybar C. Acar. The network helps show where Aybar C. Acar may publish in the future.

Co-authorship network of co-authors of Aybar C. Acar

This figure shows the co-authorship network connecting the top 25 collaborators of Aybar C. Acar. A scholar is included among the top collaborators of Aybar C. Acar 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 Aybar C. Acar. Aybar C. Acar 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.
Rifaioğlu, Ahmet Süreyya, María Martin, Rengül Çetin-Atalay, et al.. (2023). Transfer learning for drug–target interaction prediction. Bioinformatics. 39(Supplement_1). i103–i110. 35 indexed citations
2.
Acar, Aybar C., et al.. (2023). ProFAB—open protein functional annotation benchmark. Briefings in Bioinformatics. 24(2).
3.
Ataş, Heval, et al.. (2022). Learning functional properties of proteins with language models. Nature Machine Intelligence. 4(3). 227–245. 106 indexed citations
4.
Pawlowsky‐Glahn, Vera, et al.. (2022). Principal microbial groups: compositional alternative to phylogenetic grouping of microbiome data. Briefings in Bioinformatics. 23(5). 2 indexed citations
5.
Acar, Aybar C., et al.. (2022). Loss of the Nuclear Envelope Protein LAP1B Disrupts the Myogenic Differentiation of Patient-Derived Fibroblasts. International Journal of Molecular Sciences. 23(21). 13615–13615. 4 indexed citations
6.
Çetin-Atalay, Rengül, Deniz Kahraman, Ahmet Süreyya Rifaioğlu, et al.. (2021). Data Centric Molecular Analysis and Evaluation of Hepatocellular Carcinoma Therapeutics Using Machine Intelligence-Based Tools. Journal of Gastrointestinal Cancer. 52(4). 1266–1276. 2 indexed citations
7.
Gharahi, Hamidreza, et al.. (2021). Defining a master curve of abdominal aortic aneurysm growth and its potential utility of clinical management. Computer Methods and Programs in Biomedicine. 208. 106256–106256. 5 indexed citations
8.
Acar, Aybar C., et al.. (2020). Projecting the course of COVID-19 in Turkey: A probabilistic modeling approach. TURKISH JOURNAL OF MEDICAL SCIENCES. 51(1). 16–27. 7 indexed citations
9.
Acar, Aybar C., et al.. (2020). Real-time Malaria Parasite Screening in Thick Blood Smears for Low-Resource Setting. Journal of Digital Imaging. 33(3). 763–775. 29 indexed citations
10.
Acar, Aybar C., et al.. (2020). Predicting abdominal aortic aneurysm growth using patient-oriented growth models with two-step Bayesian inference. Computers in Biology and Medicine. 117. 103620–103620. 21 indexed citations
11.
Ataş, Heval, et al.. (2020). Learning Functional Properties of Proteins with Language Models. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations
12.
Acar, Aybar C., et al.. (2020). Personalized Tumor Growth Prediction Using Multiscale Modeling. Journal of Basic and Clinical Health Sciences. 1 indexed citations
13.
Rifaioğlu, Ahmet Süreyya, et al.. (2020). iBioProVis: interactive visualization and analysis of compound bioactivity space. Bioinformatics. 36(14). 4227–4230. 6 indexed citations
14.
Acar, Aybar C., et al.. (2019). The Use of Informed Priors in Biclustering of Gene Expression with the Hierarchical Dirichlet Process. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 17(5). 1810–1821. 1 indexed citations
15.
Kaya, Koray Dogan, Gökhan Karakülah, Cengiz Yakıcıer, Aybar C. Acar, & Özlen Konu. (2010). mESAdb: microRNA Expression and Sequence Analysis Database. Nucleic Acids Research. 39(suppl_1). D170–D180. 29 indexed citations
16.
Acar, Aybar C. & Amihai Motro. (2009). Efficient discovery of join plans in schemaless data. OpenMETU (Middle East Technical University). 1–1. 1 indexed citations
17.
Acar, Aybar C. & Amihai Motro. (2008). Query Consolidation: Interpreting a Set of Independent Queries Using a Multidatabase Architecture in the Reverse Direction. OpenMETU (Middle East Technical University). 4–7. 1 indexed citations
18.
Acar, Aybar C., et al.. (2005). A.: Intensional encapsulations of database subsets via genetic programming. 2 indexed citations
19.
Motro, Amihai, et al.. (2004). Utility-based resolution of data inconsistencies. OpenMETU (Middle East Technical University). 35–43. 36 indexed citations
20.
Acar, Aybar C., Hayrettin Yücel, & Ali Çulfaz. (2003). The synthesis and sodium-silver ion exchange of sodalites. Chemical Engineering Communications. 190(5-8). 861–882. 8 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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