Kaitlyn Spees

1.8k total citations
10 papers, 495 citations indexed

About

Kaitlyn Spees is a scholar working on Molecular Biology, Cell Biology and Physiology. According to data from OpenAlex, Kaitlyn Spees has authored 10 papers receiving a total of 495 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 4 papers in Cell Biology and 2 papers in Physiology. Recurrent topics in Kaitlyn Spees's work include CRISPR and Genetic Engineering (3 papers), Cellular transport and secretion (3 papers) and Protein Degradation and Inhibitors (2 papers). Kaitlyn Spees is often cited by papers focused on CRISPR and Genetic Engineering (3 papers), Cellular transport and secretion (3 papers) and Protein Degradation and Inhibitors (2 papers). Kaitlyn Spees collaborates with scholars based in United States, United Kingdom and Brazil. Kaitlyn Spees's co-authors include Michael C. Bassik, Adi Mukund, David Yao, Lacramioara Bintu, Roarke A. Kamber, Josh Tycko, Mingxin Gu, Anshul Kundaje, Peter Suzuki and Aradhana and has published in prestigious journals such as Nature, Cell and Nature Genetics.

In The Last Decade

Kaitlyn Spees

10 papers receiving 493 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kaitlyn Spees United States	9	348	99	50	48	41	10	495
K Mruk United States	8	302 0.9×	114 1.2×	34 0.7×	38 0.8×	33 0.8×	21	451
Dariel Ashton‐Beaucage Canada	8	361 1.0×	55 0.6×	25 0.5×	32 0.7×	48 1.2×	9	445
Kiran Kodali United States	10	272 0.8×	37 0.4×	47 0.9×	28 0.6×	43 1.0×	12	399
Nickolaos Nikiforos Giakoumakis Greece	10	367 1.1×	38 0.4×	57 1.1×	52 1.1×	94 2.3×	13	482
Lukas Orel Austria	14	254 0.7×	65 0.7×	26 0.5×	64 1.3×	73 1.8×	15	434
Geneviève Laroche Canada	16	374 1.1×	59 0.6×	34 0.7×	27 0.6×	93 2.3×	27	544
Kyle M. Kovary United States	7	514 1.5×	38 0.4×	53 1.1×	56 1.2×	61 1.5×	9	608
Haowen Jiang China	13	185 0.5×	93 0.9×	28 0.6×	59 1.2×	21 0.5×	20	400
Xizi Chen China	12	622 1.8×	36 0.4×	36 0.7×	38 0.8×	48 1.2×	18	719
Kimberly Larson United States	5	292 0.8×	57 0.6×	39 0.8×	71 1.5×	22 0.5×	9	382

Countries citing papers authored by Kaitlyn Spees

Since Specialization

Citations

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

Fields of papers citing papers by Kaitlyn Spees

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kaitlyn Spees

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

All Works

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10 of 10 papers shown

1.

Mitra, Koushambi, Kaitlyn Spees, AkshatKumar Nigam, et al.. (2024). An SLC12A9-dependent ion transport mechanism maintains lysosomal osmolarity. Developmental Cell. 60(2). 220–235.e7. 5 indexed citations

2.

Mukund, Adi, Josh Tycko, Stephanie A. Robinson, et al.. (2023). High-throughput functional characterization of combinations of transcriptional activators and repressors. Cell Systems. 14(9). 746–763.e5. 17 indexed citations

3.

Colville, Alex, Cristina Rodríguez-Mateo, Samantha M. Thomas, et al.. (2023). Death-seq identifies regulators of cell death and senolytic therapies. Cell Metabolism. 35(10). 1814–1829.e6. 18 indexed citations

4.

DelRosso, Nicole, Josh Tycko, Peter Suzuki, et al.. (2023). Large-scale mapping and mutagenesis of human transcriptional effector domains. Nature. 616(7956). 365–372. 72 indexed citations

5.

Dong, Wentao, Ali Ghoochani, Kwamina Nyame, et al.. (2023). An SPNS1-dependent lysosomal lipid transport pathway that enables cell survival under choline limitation. Science Advances. 9(16). eadf8966–eadf8966. 26 indexed citations

6.

Kamber, Roarke A., Yoko Nishiga, Allison Banuelos, et al.. (2021). Inter-cellular CRISPR screens reveal regulators of cancer cell phagocytosis. Nature. 597(7877). 549–554. 118 indexed citations

7.

Wainberg, Michael, Roarke A. Kamber, Akshay Balsubramani, et al.. (2021). A genome-wide atlas of co-essential modules assigns function to uncharacterized genes. Nature Genetics. 53(5). 638–649. 103 indexed citations

8.

Kelly, Marcus R., Kaja Kostyrko, Kyuho Han, et al.. (2020). Combined Proteomic and Genetic Interaction Mapping Reveals New RAS Effector Pathways and Susceptibilities. Cancer Discovery. 10(12). 1950–1967. 30 indexed citations

9.

Tycko, Josh, Nicole DelRosso, Gaelen T. Hess, et al.. (2020). High-Throughput Discovery and Characterization of Human Transcriptional Effectors. Cell. 183(7). 2020–2035.e16. 79 indexed citations

10.

Cooke, Thomas F., L. Elaine Epperson, Kaitlyn Spees, et al.. (2019). Genetic variation drives seasonal onset of hibernation in the 13-lined ground squirrel. Communications Biology. 2(1). 478–478. 27 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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