Aleksandrina Goeva

6.0k total citations · 3 hit papers
12 papers, 3.0k citations indexed

About

Aleksandrina Goeva is a scholar working on Molecular Biology, Management Science and Operations Research and Statistics, Probability and Uncertainty. According to data from OpenAlex, Aleksandrina Goeva has authored 12 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Management Science and Operations Research and 3 papers in Statistics, Probability and Uncertainty. Recurrent topics in Aleksandrina Goeva's work include Single-cell and spatial transcriptomics (4 papers), Simulation Techniques and Applications (3 papers) and Advanced Queuing Theory Analysis (2 papers). Aleksandrina Goeva is often cited by papers focused on Single-cell and spatial transcriptomics (4 papers), Simulation Techniques and Applications (3 papers) and Advanced Queuing Theory Analysis (2 papers). Aleksandrina Goeva collaborates with scholars based in United States, Israel and Canada. Aleksandrina Goeva's co-authors include Evan Z. Macosko, Evan Murray, Fei Chen, Caroline Martin, Joshua D. Welch, Samuel G. Rodriques, Robert R. Stickels, Charles Vanderburg, Rafael A. Irizarry and Luli S. Zou and has published in prestigious journals such as Science, Cell and Nature Communications.

In The Last Decade

Aleksandrina Goeva

12 papers receiving 2.9k citations

Hit Papers

Slide-seq: A scalable technology for measuring genome-wid... 2018 2026 2020 2023 2019 2018 2021 400 800 1.2k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution
    2019 1.4k citations Samuel G. Rodriques, Robert R. Stickels et al. Science profile →
  2. Molecular Diversity and Specializations among the Cells of the Adult Mouse Brain
    2018 943 citations Arpiar Saunders, Evan Z. Macosko et al. Cell profile →
  3. Robust decomposition of cell type mixtures in spatial transcriptomics
    2021 565 citations Dylan Cable, Evan Murray et al. Nature Biotechnology profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Aleksandrina Goeva United States 7 2.3k 537 407 381 372 12 3.0k
Lars E. Borm Sweden 10 2.1k 0.9× 364 0.7× 560 1.4× 317 0.8× 243 0.7× 12 3.1k
Caroline Martin United States 6 2.0k 0.9× 420 0.8× 204 0.5× 352 0.9× 377 1.0× 6 2.4k
Spyros Darmanis United States 26 2.7k 1.2× 942 1.8× 1.0k 2.5× 279 0.7× 614 1.7× 45 4.7k
Aparna Bhaduri United States 27 2.6k 1.1× 657 1.2× 489 1.2× 155 0.4× 538 1.4× 58 4.1k
Charlotte Rolny Sweden 22 2.5k 1.1× 1.0k 1.9× 623 1.5× 206 0.5× 551 1.5× 34 4.1k
Jamie L. Marshall United States 22 2.0k 0.9× 382 0.7× 430 1.1× 146 0.4× 292 0.8× 30 2.9k
Stephen W. Eichhorn United States 13 2.2k 1.0× 234 0.4× 177 0.4× 192 0.5× 505 1.4× 16 2.8k
Yun C. Yung United States 22 3.3k 1.4× 418 0.8× 451 1.1× 85 0.2× 443 1.2× 30 4.3k
Qiaolin Deng Sweden 28 4.2k 1.8× 581 1.1× 214 0.5× 313 0.8× 1.0k 2.7× 56 5.5k
Lucas T. Graybuck United States 7 1.1k 0.5× 199 0.4× 158 0.4× 168 0.4× 202 0.5× 8 1.6k

Countries citing papers authored by Aleksandrina Goeva

Since Specialization
Citations

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

Fields of papers citing papers by Aleksandrina Goeva

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aleksandrina Goeva

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

All Works

12 of 12 papers shown
1.
Yang, Andy, Rony Chidiac, Hendrik W. Steenland, et al.. (2024). Exploiting spatiotemporal regulation of FZD5 during neural patterning for efficient ventral midbrain specification. Development. 151(5). 6 indexed citations
2.
Goeva, Aleksandrina, Michael-John Dolan, Judy Luu, et al.. (2024). HiDDEN: a machine learning method for detection of disease-relevant populations in case-control single-cell transcriptomics data. Nature Communications. 15(1). 9468–9468. 6 indexed citations
3.
Adler, Miri, Aleksandrina Goeva, Inbal Avraham‐Davidi, et al.. (2023). Emergence of division of labor in tissues through cell interactions and spatial cues. Cell Reports. 42(5). 112412–112412. 16 indexed citations
4.
Cable, Dylan, Evan Murray, Luli S. Zou, et al.. (2021). Robust decomposition of cell type mixtures in spatial transcriptomics. Nature Biotechnology. 40(4). 517–526. 565 indexed citations breakdown →
5.
Goeva, Aleksandrina, et al.. (2020). Toward Reproducible and Extensible Research: from Values to Action. SHILAP Revista de lepidopterología. 2(4). 8 indexed citations
6.
Rodriques, Samuel G., Robert R. Stickels, Aleksandrina Goeva, et al.. (2019). Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution. Science. 363(6434). 1463–1467. 1378 indexed citations breakdown →
7.
Goeva, Aleksandrina, et al.. (2019). Optimization-Based Calibration of Simulation Input Models. Operations Research. 67(5). 1362–1382. 8 indexed citations
8.
Kramer, Jessica M., Christine A. Helfrich, Ariel Schwartz, et al.. (2019). Outcomes of an Environmental-Focused, Problem-Solving Intervention for Transition-Age Youth: Project TEAM. American Journal of Occupational Therapy. 73(4_Supplement_1). 7311515321p1–7311515321p1. 1 indexed citations
9.
Saunders, Arpiar, Evan Z. Macosko, Alec Wysoker, et al.. (2018). Molecular Diversity and Specializations among the Cells of the Adult Mouse Brain. Cell. 174(4). 1015–1030.e16. 943 indexed citations breakdown →
10.
Kramer, Jessica M., Christine A. Helfrich, Preethy S. Samuel, et al.. (2018). Initial evaluation of the effects of an environmental‐focused problem‐solving intervention for transition‐age young people with developmental disabilities: Project TEAM. Developmental Medicine & Child Neurology. 60(8). 801–809. 28 indexed citations
11.
Goeva, Aleksandrina, Henry Lam, & Bo Zhang. (2014). Reconstructing input models via simulation optimization. Winter Simulation Conference. 698–709. 2 indexed citations
12.
Goeva, Aleksandrina, Henry Lam, & Bo Zhang. (2014). Reconstructing input models via simulation optimization. Proceedings of the Winter Simulation Conference 2014. 698–709. 3 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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