J. Landis

2.1k total citations
29 papers, 1.5k citations indexed

About

J. Landis is a scholar working on Pediatrics, Perinatology and Child Health, Molecular Biology and Public Health, Environmental and Occupational Health. According to data from OpenAlex, J. Landis has authored 29 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Pediatrics, Perinatology and Child Health, 10 papers in Molecular Biology and 10 papers in Public Health, Environmental and Occupational Health. Recurrent topics in J. Landis's work include Reproductive Biology and Fertility (8 papers), Prenatal Screening and Diagnostics (8 papers) and Genetics, Aging, and Longevity in Model Organisms (6 papers). J. Landis is often cited by papers focused on Reproductive Biology and Fertility (8 papers), Prenatal Screening and Diagnostics (8 papers) and Genetics, Aging, and Longevity in Model Organisms (6 papers). J. Landis collaborates with scholars based in United States, United Kingdom and Denmark. J. Landis's co-authors include Coleen T. Murphy, Jasmine M. Ashraf, Richard T. Scott, Xin Tao, Nathan R. Treff, T. Keith Blackwell, Riva de Paula Oliveira, Kieran Dilks, Shijing Luo and Amanda Kauffman and has published in prestigious journals such as Nature, Current Biology and PLoS Biology.

In The Last Decade

J. Landis

29 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
J. Landis United States 16 782 604 330 223 222 29 1.5k
Lesley T. MacNeil Canada 20 791 1.0× 1.1k 1.8× 205 0.6× 217 1.0× 77 0.3× 32 1.8k
Huatao Chen China 23 113 0.1× 276 0.5× 421 1.3× 182 0.8× 136 0.6× 69 1.1k
Guoshi Liu China 29 182 0.2× 667 1.1× 877 2.7× 221 1.0× 1.1k 5.0× 113 2.7k
Kyu-Tae Chang South Korea 18 55 0.1× 440 0.7× 62 0.2× 139 0.6× 164 0.7× 40 954
April E. Williams United States 15 298 0.4× 742 1.2× 185 0.6× 218 1.0× 636 2.9× 21 1.6k
Sara de Mateo Spain 15 114 0.1× 456 0.8× 435 1.3× 399 1.8× 530 2.4× 20 1.5k
Rebecca I. Clark United Kingdom 13 372 0.5× 570 0.9× 80 0.2× 224 1.0× 86 0.4× 15 1.5k
Karen Plaut United States 21 46 0.1× 459 0.8× 173 0.5× 221 1.0× 45 0.2× 65 1.5k
Pengyun Ji China 17 113 0.1× 313 0.5× 458 1.4× 124 0.6× 621 2.8× 50 1.3k

Countries citing papers authored by J. Landis

Since Specialization
Citations

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

Fields of papers citing papers by J. Landis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J. Landis

This figure shows the co-authorship network connecting the top 25 collaborators of J. Landis. A scholar is included among the top collaborators of J. Landis 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 J. Landis. J. Landis 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.
2.
Tiegs, Ashley W., Xin Tao, J. Landis, et al.. (2020). Sperm Mitochondrial DNA Copy Number Is Not a Predictor of Intracytoplasmic Sperm Injection (ICSI) Cycle Outcomes. Reproductive Sciences. 27(6). 1350–1356. 10 indexed citations
3.
Tiegs, Ashley W., J. Landis, Nicolás Garrido, Richard T. Scott, & James M. Hotaling. (2019). Total Motile Sperm Count Trend Over Time: Evaluation of Semen Analyses From 119,972 Men From Subfertile Couples. Urology. 132. 109–116. 45 indexed citations
4.
Franasiak, Jason M., M.D. Werner, Xin Tao, et al.. (2018). Cumulus cell transcriptome profiling is not predictive of live birth after in vitro fertilization: a paired analysis of euploid sibling blastocysts. Fertility and Sterility. 109(3). 460–466.e2. 26 indexed citations
5.
Tiegs, Ashley W., J. Landis, Nicolás Garrido, Richard T. Scott, & James M. Hotaling. (2018). Total motile sperm count trend over time across two continents: evaluation of semen analyses from 119,972 infertile men. Fertility and Sterility. 110(4). e27–e27. 4 indexed citations
6.
7.
Chattopadhyay, Ratna, C.R. Juneau, J. Landis, et al.. (2017). Persistent fluid in the endometrial cavity that resolves after progesterone administration prior to transfer does impact live birth rate. Fertility and Sterility. 107(3). e11–e11. 1 indexed citations
8.
Goodrich, David W., Tongji Xing, Xin Tao, et al.. (2017). Evaluation of comprehensive chromosome screening platforms for the detection of mosaic segmental aneuploidy. Journal of Assisted Reproduction and Genetics. 34(8). 975–981. 38 indexed citations
9.
Tao, Xin, J. Landis, Rebecca L. Krisher, et al.. (2017). Mitochondrial DNA content is associated with ploidy status, maternal age, and oocyte maturation methods in mouse blastocysts. Journal of Assisted Reproduction and Genetics. 34(12). 1587–1594. 13 indexed citations
10.
Morin, S.J., Ashley W. Tiegs, Jason M. Franasiak, et al.. (2016). FMR1 gene CGG repeat variation within the normal range is not predictive of ovarian response in IVF cycles. Reproductive BioMedicine Online. 32(5). 496–502. 10 indexed citations
11.
Wang, Juan, Rachel Kaletsky, Malan Silva, et al.. (2015). Cell-Specific Transcriptional Profiling of Ciliated Sensory Neurons Reveals Regulators of Behavior and Extracellular Vesicle Biogenesis. Current Biology. 25(24). 3232–3238. 68 indexed citations
12.
Franasiak, Jason M., M.D. Werner, C.R. Juneau, et al.. (2015). Endometrial microbiome at the time of embryo transfer: next-generation sequencing of the 16S ribosomal subunit. Journal of Assisted Reproduction and Genetics. 33(1). 129–136. 205 indexed citations
13.
Kaletsky, Rachel, Vanisha Lakhina, Rachel N. Arey, et al.. (2015). The C. elegans adult neuronal IIS/FOXO transcriptome reveals adult phenotype regulators. Nature. 529(7584). 92–96. 164 indexed citations
14.
Goodrich, David W., Xueying Tao, James E. J. Bedard, et al.. (2015). Evaluation of Next Generation Sequencing (NGS) based comprehensive chromosome screening (CCS) sensitivity to mosaicism. Fertility and Sterility. 104(3). e280–e281. 1 indexed citations
15.
Franasiak, Jason M., M.D. Werner, C.R. Juneau, et al.. (2015). Microbiome at the time of embryo transfer: next generation sequencing of the 16S ribosomal subunit. Fertility and Sterility. 104(3). e54–e55. 3 indexed citations
16.
Kauffman, Amanda, Jasmine M. Ashraf, M. Ryan Corces, J. Landis, & Coleen T. Murphy. (2010). Insulin Signaling and Dietary Restriction Differentially Influence the Decline of Learning and Memory with Age. PLoS Biology. 8(5). e1000372–e1000372. 184 indexed citations
17.
Landis, J. & Coleen T. Murphy. (2010). Integration of diverse inputs in the regulation of Caenorhabditis elegans DAF‐16/FOXO. Developmental Dynamics. 239(5). 1405–1412. 71 indexed citations
18.
Oliveira, Riva de Paula, Kieran Dilks, J. Landis, et al.. (2009). Condition‐adapted stress and longevity gene regulation by Caenorhabditis elegans SKN‐1/Nrf. Aging Cell. 8(5). 524–541. 283 indexed citations
19.
Luo, Shijing, et al.. (2007). The C. elegans TGF-β Dauer Pathway Regulates Longevity via Insulin Signaling. Current Biology. 17(19). 1635–1645. 190 indexed citations
20.
Huttenhower, Curtis, Avi I. Flamholz, J. Landis, et al.. (2007). Nearest Neighbor Networks: clustering expression data based on gene neighborhoods. BMC Bioinformatics. 8(1). 250–250. 52 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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