Padideh Danaee

675 total citations
5 papers, 382 citations indexed

About

Padideh Danaee is a scholar working on Molecular Biology, Artificial Intelligence and Cancer Research. According to data from OpenAlex, Padideh Danaee has authored 5 papers receiving a total of 382 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 2 papers in Artificial Intelligence and 1 paper in Cancer Research. Recurrent topics in Padideh Danaee's work include RNA and protein synthesis mechanisms (2 papers), RNA modifications and cancer (1 paper) and Cancer-related molecular mechanisms research (1 paper). Padideh Danaee is often cited by papers focused on RNA and protein synthesis mechanisms (2 papers), RNA modifications and cancer (1 paper) and Cancer-related molecular mechanisms research (1 paper). Padideh Danaee collaborates with scholars based in United States. Padideh Danaee's co-authors include David A. Hendrix, Reza Ghaeini, Liang Huang, Steven T. Hill, Rachael Kuintzle and Phillip Wallis and has published in prestigious journals such as Nucleic Acids Research, PubMed and The Florida AI Research Society.

In The Last Decade

Padideh Danaee

5 papers receiving 369 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Padideh Danaee United States	3	290	106	61	33	21	5	382
Milad Mostavi United States	6	221 0.8×	106 1.0×	76 1.2×	49 1.5×	18 0.9×	6	334
Nimrod Rappoport Israel	7	497 1.7×	63 0.6×	128 2.1×	20 0.6×	21 1.0×	8	630
Ping Luo Canada	11	249 0.9×	46 0.4×	67 1.1×	39 1.2×	12 0.6×	24	363
Reza Ghaeini United States	4	114 0.4×	161 1.5×	23 0.4×	33 1.0×	28 1.3×	5	253
Qinhu Zhang China	11	488 1.7×	39 0.4×	74 1.2×	16 0.5×	18 0.9×	42	582
Safiye Çelik United States	8	146 0.5×	53 0.5×	47 0.8×	35 1.1×	22 1.0×	11	316
Aidan N. Gomez Canada	2	257 0.9×	58 0.5×	48 0.8×	15 0.5×	54 2.6×	3	442
Chunhui Cai United States	7	139 0.5×	36 0.3×	39 0.6×	29 0.9×	6 0.3×	21	212
Le Yang China	9	215 0.7×	64 0.6×	94 1.5×	10 0.3×	20 1.0×	21	288
Pierre Machart Germany	6	175 0.6×	36 0.3×	27 0.4×	32 1.0×	15 0.7×	9	228

Countries citing papers authored by Padideh Danaee

Since Specialization

Citations

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

Fields of papers citing papers by Padideh Danaee

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Padideh Danaee

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

All Works

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5 of 5 papers shown

1.

Wallis, Phillip & Padideh Danaee. (2019). Learning Semantic Relationships from Medical Codes.. The Florida AI Research Society. 305–310. 1 indexed citations

2.

Danaee, Padideh. (2019). Interpretable Machine Learning: Applications in Biology and Genomics. 1 indexed citations

3.

Danaee, Padideh, et al.. (2018). bpRNA: large-scale automated annotation and analysis of RNA secondary structure. Nucleic Acids Research. 46(11). 5381–5394. 129 indexed citations

4.

Hill, Steven T., et al.. (2018). A deep recurrent neural network discovers complex biological rules to decipher RNA protein-coding potential. Nucleic Acids Research. 46(16). 8105–8113. 60 indexed citations

5.

Danaee, Padideh, Reza Ghaeini, & David A. Hendrix. (2016). A DEEP LEARNING APPROACH FOR CANCER DETECTION AND RELEVANT GENE IDENTIFICATION. PubMed. 22. 219–229. 191 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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