E. Jane Albert Hubbard

4.1k total citations
65 papers, 3.0k citations indexed

About

E. Jane Albert Hubbard is a scholar working on Aging, Molecular Biology and Endocrine and Autonomic Systems. According to data from OpenAlex, E. Jane Albert Hubbard has authored 65 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Aging, 38 papers in Molecular Biology and 22 papers in Endocrine and Autonomic Systems. Recurrent topics in E. Jane Albert Hubbard's work include Genetics, Aging, and Longevity in Model Organisms (52 papers), Circadian rhythm and melatonin (22 papers) and Reproductive Biology and Fertility (15 papers). E. Jane Albert Hubbard is often cited by papers focused on Genetics, Aging, and Longevity in Model Organisms (52 papers), Circadian rhythm and melatonin (22 papers) and Reproductive Biology and Fertility (15 papers). E. Jane Albert Hubbard collaborates with scholars based in United States, Israel and United Kingdom. E. Jane Albert Hubbard's co-authors include Darrell J. Killian, David Greenstein, Marian Carlson, Dorota Z. Korta, Tim Schedl, Iva Greenwald, David Michaelson, Xiaolu Yang, Roumen Voutev and Jan Kitajewski and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

E. Jane Albert Hubbard

62 papers receiving 3.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
E. Jane Albert Hubbard United States 32 1.9k 1.9k 587 582 257 65 3.0k
Alex Hajnal Switzerland 27 1.4k 0.7× 1.1k 0.6× 254 0.4× 404 0.7× 520 2.0× 71 2.4k
Rueyling Lin United States 25 2.5k 1.3× 1.4k 0.8× 626 1.1× 184 0.3× 724 2.8× 39 3.2k
Gino Poulin United Kingdom 19 2.8k 1.4× 1.9k 1.0× 194 0.3× 404 0.7× 469 1.8× 32 4.0k
John Yochem United States 25 1.8k 0.9× 1.0k 0.6× 170 0.3× 330 0.6× 422 1.6× 36 2.6k
Alexander Kanapin Russia 15 3.1k 1.6× 1.7k 0.9× 181 0.3× 330 0.6× 423 1.6× 58 4.3k
David S. Fay United States 29 1.8k 1.0× 1.0k 0.5× 173 0.3× 239 0.4× 467 1.8× 73 2.6k
Jordan D. Ward United States 24 2.6k 1.4× 1.5k 0.8× 126 0.2× 319 0.5× 413 1.6× 43 3.3k
Barbara Conradt Germany 32 2.6k 1.4× 1.5k 0.8× 147 0.3× 274 0.5× 765 3.0× 72 3.6k
H. Robert Horvitz United States 14 2.7k 1.4× 1.4k 0.7× 246 0.4× 552 0.9× 455 1.8× 16 4.3k
Nathalie Le Bot United States 12 3.1k 1.6× 1.8k 1.0× 220 0.4× 350 0.6× 1.2k 4.7× 22 4.3k

Countries citing papers authored by E. Jane Albert Hubbard

Since Specialization
Citations

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

Fields of papers citing papers by E. Jane Albert Hubbard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by E. Jane Albert Hubbard. 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 E. Jane Albert Hubbard. The network helps show where E. Jane Albert Hubbard may publish in the future.

Co-authorship network of co-authors of E. Jane Albert Hubbard

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

All Works

20 of 20 papers shown
1.
Кryvoruchko, І. А., et al.. (2025). Artificial Intelligence-Based Quality Control of Cell Lines. Biopreservation and Biobanking.
2.
Hubbard, E. Jane Albert, et al.. (2025). Non-autonomy of age-related morphological changes in the C. elegans germline stem cell niche. Development. 152(20).
3.
4.
Hubbard, E. Jane Albert, et al.. (2022). Modeling the C. elegans germline stem cell genetic network using automated reasoning. Biosystems. 217. 104672–104672.
5.
Hubbard, E. Jane Albert, et al.. (2021). Germline Stem and Progenitor Cell Aging in C. elegans. Frontiers in Cell and Developmental Biology. 9. 699671–699671. 14 indexed citations
6.
Jordan, James M., Jonathan D. Hibshman, Amy K. Webster, et al.. (2019). Insulin/IGF Signaling and Vitellogenin Provisioning Mediate Intergenerational Adaptation to Nutrient Stress. Current Biology. 29(14). 2380–2388.e5. 41 indexed citations
7.
Vallier, Ludovic, et al.. (2018). The DSL ligand APX-1 is required for normal ovulation in C. elegans. Developmental Biology. 435(2). 162–169. 6 indexed citations
8.
Ow, Maria C., et al.. (2017). Linking the environment, DAF-7/TGFβ signaling and LAG-2/DSL ligand expression in the germline stem cell niche. Development. 144(16). 2896–2906. 31 indexed citations
9.
Vogel, Julia Moore, David Michaelson, Anthony Santella, E. Jane Albert Hubbard, & Zhirong Bao. (2014). Irises. PubMed. 3(2). e29041–e29041. 4 indexed citations
10.
Hubbard, E. Jane Albert, et al.. (2012). Physiological Control of Germline Development. Advances in experimental medicine and biology. 757. 101–131. 47 indexed citations
11.
Voutev, Roumen, et al.. (2009). A “latent niche” mechanism for tumor initiation. Proceedings of the National Academy of Sciences. 106(28). 11617–11622. 71 indexed citations
12.
Nadarajan, Saravanapriah, et al.. (2009). MSP and GLP-1/Notch signaling coordinately regulate actomyosin-dependent cytoplasmic streaming and oocyte growth in C. elegans. Development. 136(13). 2223–2234. 110 indexed citations
13.
Kam, Naaman, Hillel Kugler, Rami Marelly, et al.. (2008). A scenario-based approach to modeling development: A prototype model of C. elegans vulval fate specification. Developmental Biology. 323(1). 1–5. 22 indexed citations
14.
Killian, Darrell J. & E. Jane Albert Hubbard. (2005). Caenorhabditis elegans germline patterning requires coordinated development of the somatic gonadal sheath and the germ line. Developmental Biology. 279(2). 322–335. 94 indexed citations
15.
Killian, Darrell J. & E. Jane Albert Hubbard. (2004). C. elegans pro-1 activity is required for soma/germline interactions that influence proliferation and differentiation in the germ line. Development. 131(6). 1267–1278. 46 indexed citations
16.
Hansen, Dave, E. Jane Albert Hubbard, & Tim Schedl. (2004). Multi-pathway control of the proliferation versus meiotic development decision in the Caenorhabditis elegans germline. Developmental Biology. 268(2). 342–357. 132 indexed citations
17.
Hubbard, E. Jane Albert & David Greenstein. (2000). TheCaenorhabditis elegans gonad: A test tube for cell and developmental biology. Developmental Dynamics. 218(1). 2–22. 193 indexed citations
18.
Hubbard, E. Jane Albert, Rong Jiang, & Marian Carlson. (1994). Dosage-Dependent Modulation of Glucose Repression by MSN3 (STD1) in Saccharomyces cerevisiae. Molecular and Cellular Biology. 14(3). 1972–1978. 16 indexed citations
19.
Hubbard, E. Jane Albert, R. Jiang, & Marian Carlson. (1994). Dosage-dependent modulation of glucose repression by MSN3 (STD1) in Saccharomyces cerevisiae.. Molecular and Cellular Biology. 14(3). 1972–1978. 41 indexed citations
20.
Hartshorn, Michael J. & E. Jane Albert Hubbard. (1993). Interactive protein modelling. 25–32. 1 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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