Michele E. Day

406 total citations
5 papers, 195 citations indexed

About

Michele E. Day is a scholar working on Molecular Biology, Artificial Intelligence and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Michele E. Day has authored 5 papers receiving a total of 195 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Molecular Biology, 2 papers in Artificial Intelligence and 1 paper in Cardiology and Cardiovascular Medicine. Recurrent topics in Michele E. Day's work include Ethics in Clinical Research (1 paper), Protein Kinase Regulation and GTPase Signaling (1 paper) and Meta-analysis and systematic reviews (1 paper). Michele E. Day is often cited by papers focused on Ethics in Clinical Research (1 paper), Protein Kinase Regulation and GTPase Signaling (1 paper) and Meta-analysis and systematic reviews (1 paper). Michele E. Day collaborates with scholars based in United States. Michele E. Day's co-authors include Lucila Ohno‐Machado, Claudiu Farcas, Michael E. Matheny, Xiaoqian Jiang, Frederic S. Resnic, Aziz A. Boxwala, Hyeoneui Kim, Brian E. Chapman, Kamalika Chaudhuri and Ji‐Hoon Kim and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Cell Biology and Journal of the American Medical Informatics Association.

In The Last Decade

Michele E. Day

5 papers receiving 190 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michele E. Day United States	5	103	63	29	22	19	5	195
Matthias Ganzinger Germany	9	87 0.8×	62 1.0×	76 2.6×	51 2.3×	17 0.9×	35	281
Peter O’Blenis Canada	6	50 0.5×	92 1.5×	31 1.1×	14 0.6×	21 1.1×	11	274
Christoph Havemann Germany	6	40 0.4×	22 0.3×	41 1.4×	14 0.6×	12 0.6×	6	147
Lewis J. Frey United States	11	113 1.1×	117 1.9×	15 0.5×	49 2.2×	28 1.5×	41	340
Johannes Starlinger Germany	9	125 1.2×	121 1.9×	12 0.4×	8 0.4×	19 1.0×	16	258
Karen He United States	6	83 0.8×	29 0.5×	21 0.7×	23 1.0×	46 2.4×	12	230
Girish Chavan United States	5	156 1.5×	167 2.7×	13 0.4×	26 1.2×	18 0.9×	7	252
Alexander Bartschke Germany	3	35 0.3×	40 0.6×	29 1.0×	47 2.1×	6 0.3×	6	159
Stefan Hegselmann Germany	6	43 0.4×	132 2.1×	11 0.4×	29 1.3×	6 0.3×	18	233
Anja Wulf United States	12	187 1.8×	30 0.5×	75 2.6×	7 0.3×	60 3.2×	14	445

Countries citing papers authored by Michele E. Day

Since Specialization

Citations

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

Fields of papers citing papers by Michele E. Day

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michele E. Day. 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 Michele E. Day. The network helps show where Michele E. Day may publish in the future.

Co-authorship network of co-authors of Michele E. Day

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

All Works

Sort: Min cites: Since: Top N: Style:

5 of 5 papers shown

1.

Kuo, Tsung-Ting, Cleo K. Maehara, Son Doan, et al.. (2016). Ensembles of NLP Tools for Data Element Extraction from Clinical Notes.. PubMed. 2016. 1880–1889. 19 indexed citations

2.

Meeker, Daniella, Xiaoqian Jiang, Michael E. Matheny, et al.. (2015). A system to build distributed multivariate models and manage disparate data sharing policies: implementation in the scalable national network for effectiveness research. Journal of the American Medical Informatics Association. 22(6). 1187–1195. 15 indexed citations

3.

Haushalter, Kristofer J., Mathivadhani Panneerselvam, Philip Chang, et al.. (2013). A kinase interacting protein (AKIP1) is a key regulator of cardiac stress. Proceedings of the National Academy of Sciences. 110(5). E387–96. 30 indexed citations

4.

Ohno‐Machado, Lucila, Vineet Bafna, Aziz A. Boxwala, et al.. (2011). iDASH: integrating data for analysis, anonymization, and sharing. Journal of the American Medical Informatics Association. 19(2). 196–201. 95 indexed citations

5.

Day, Michele E., Guido Gaietta, Antonius Koller, et al.. (2011). Isoform-specific targeting of PKA to multivesicular bodies. The Journal of Cell Biology. 193(2). 347–363. 36 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.

Explore authors with similar magnitude of impact