Miloš Babić

574 total citations
9 papers, 403 citations indexed

About

Miloš Babić is a scholar working on Molecular Biology, Cell Biology and Oncology. According to data from OpenAlex, Miloš Babić has authored 9 papers receiving a total of 403 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Cell Biology and 2 papers in Oncology. Recurrent topics in Miloš Babić's work include Mitochondrial Function and Pathology (2 papers), Molecular Biology Techniques and Applications (2 papers) and Cellular transport and secretion (2 papers). Miloš Babić is often cited by papers focused on Mitochondrial Function and Pathology (2 papers), Molecular Biology Techniques and Applications (2 papers) and Cellular transport and secretion (2 papers). Miloš Babić collaborates with scholars based in United States and France. Miloš Babić's co-authors include Konrad E. Zinsmaier, Jialie Luo, John F. Hancock, Ching‐On Wong, Kartik Venkatachalam, Yong Zhou, Hongzhen Hu, Liang Hong, Michael X. Zhu and Dharini van der Hoeven and has published in prestigious journals such as Science, Journal of Neuroscience and PLoS ONE.

In The Last Decade

Miloš Babić

8 papers receiving 399 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Miloš Babić United States	6	298	83	68	41	39	9	403
Ginam Cho United States	15	440 1.5×	104 1.3×	110 1.6×	41 1.0×	51 1.3×	27	645
Mário F. Neto United States	8	281 0.9×	83 1.0×	89 1.3×	62 1.5×	33 0.8×	12	494
Radha Desai United States	12	386 1.3×	82 1.0×	91 1.3×	49 1.2×	33 0.8×	14	545
Rossana Foti Italy	9	455 1.5×	66 0.8×	34 0.5×	45 1.1×	24 0.6×	10	525
Haiping Que China	12	181 0.6×	61 0.7×	83 1.2×	24 0.6×	36 0.9×	24	323
Ruth E. Carmichael United Kingdom	12	313 1.1×	66 0.8×	53 0.8×	55 1.3×	43 1.1×	21	401
Tomoko Sayano Japan	10	396 1.3×	65 0.8×	73 1.1×	84 2.0×	41 1.1×	12	528
Jiyeon Ohk South Korea	9	454 1.5×	80 1.0×	123 1.8×	18 0.4×	37 0.9×	12	550
Abigail Buchwalter United States	8	463 1.6×	93 1.1×	45 0.7×	43 1.0×	18 0.5×	15	537
Dmitrij Lisak Germany	8	238 0.8×	68 0.8×	35 0.5×	28 0.7×	69 1.8×	8	408

Countries citing papers authored by Miloš Babić

Since Specialization

Citations

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

Fields of papers citing papers by Miloš Babić

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Miloš Babić

This figure shows the co-authorship network connecting the top 25 collaborators of Miloš Babić. A scholar is included among the top collaborators of Miloš Babić 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 Miloš Babić. Miloš Babić 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:

9 of 9 papers shown

1.

Babić, Miloš, et al.. (2024). 8269 Euglycemic Diabetic Ketoacidosis Secondary to Rapid Weight Loss in a Patient on Dapagliflozin. Journal of the Endocrine Society. 8(Supplement_1).

2.

Aloysius, Mark M., et al.. (2022). Racial and ethnic characteristics and cancer-specific survival in Primary Malignant Cardiac Tumors. Frontiers in Cardiovascular Medicine. 9. 961160–961160. 4 indexed citations

3.

Trejo, Christy L., Miloš Babić, Elliot Imler, et al.. (2019). Extraction-free whole transcriptome gene expression analysis of FFPE sections and histology-directed subareas of tissue. PLoS ONE. 14(2). e0212031–e0212031. 25 indexed citations

4.

Chappell, Grace A., Julia E. Rager, Jeffrey C. Wolf, et al.. (2019). Comparison of Gene Expression Responses in the Small Intestine of Mice Following Exposure to 3 Carcinogens Using the S1500+ Gene Set Informs a Potential Common Adverse Outcome Pathway. Toxicologic Pathology. 47(7). 851–864. 6 indexed citations

5.

Trejo, Christy L., Elliot Imler, Miloš Babić, et al.. (2019). Abstract 5241: Whole transcriptome TempO-Seq profiling of focal areas of H&E stained FFPE: Differentiation of normal colon and cancer phenotypes between donors. Cancer Research. 79(13_Supplement). 5241–5241. 1 indexed citations

6.

Babić, Miloš, et al.. (2015). Miro's N-Terminal GTPase Domain Is Required for Transport of Mitochondria into Axons and Dendrites. Journal of Neuroscience. 35(14). 5754–5771. 54 indexed citations

7.

Zhou, Yong, Ching‐On Wong, Kwang-Jin Cho, et al.. (2015). Membrane potential modulates plasma membrane phospholipid dynamics and K-Ras signaling. Science. 349(6250). 873–876. 235 indexed citations

8.

Tsai, Pei‐I, et al.. (2014). PINK1-mediated Phosphorylation of Miro Inhibits Synaptic Growth and Protects Dopaminergic Neurons in Drosophila. Scientific Reports. 4(1). 6962–6962. 37 indexed citations

9.

Zinsmaier, Konrad E., et al.. (2009). Mitochondrial Transport Dynamics in Axons and Dendrites. Results and problems in cell differentiation. 48. 361–381. 41 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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