Tyler J. Moss

4.1k total citations · 1 hit paper
20 papers, 2.4k citations indexed

About

Tyler J. Moss is a scholar working on Molecular Biology, Cancer Research and Cell Biology. According to data from OpenAlex, Tyler J. Moss has authored 20 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 10 papers in Cancer Research and 7 papers in Cell Biology. Recurrent topics in Tyler J. Moss's work include Cellular transport and secretion (7 papers), MicroRNA in disease regulation (5 papers) and Cancer-related molecular mechanisms research (4 papers). Tyler J. Moss is often cited by papers focused on Cellular transport and secretion (7 papers), MicroRNA in disease regulation (5 papers) and Cancer-related molecular mechanisms research (4 papers). Tyler J. Moss collaborates with scholars based in United States, Italy and Japan. Tyler J. Moss's co-authors include James A. McNew, Prahlad T. Ram, Deepak Nagrath, Lifeng Yang, Elena G. Seviour, Andrea Daga, Juan C. Marini, Abhinav Achreja, Hongyun Zhao and Donna M. Peehl and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Tyler J. Moss

20 papers receiving 2.4k citations

Hit Papers

Tumor microenvironment derived exosomes pleiotropically m... 2016 2026 2019 2022 2016 200 400 600

Peers

Tyler J. Moss
Dean Yimlamai United States
Guang‐Hui Xiao United States
Qiong Lin China
Leslie A. Goldstein United States
Myriam Boukhali United States
Irene K. Yan United States
Tyler J. Moss
Citations per year, relative to Tyler J. Moss Tyler J. Moss (= 1×) peers Roser Pinyol

Countries citing papers authored by Tyler J. Moss

Since Specialization
Citations

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

Fields of papers citing papers by Tyler J. Moss

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tyler J. Moss

This figure shows the co-authorship network connecting the top 25 collaborators of Tyler J. Moss. A scholar is included among the top collaborators of Tyler J. Moss 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 Tyler J. Moss. Tyler J. Moss 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.
Petros, Firas G., Woonyoung Choi, Yuan Qi, et al.. (2021). Expression Analysis of Same-Patient Metachronous and Synchronous Upper Tract and Bladder Urothelial Carcinoma. The Journal of Urology. 206(3). 548–557. 8 indexed citations
2.
Moss, Tyler J., Jordi Rodón, Holly D. Oakley, et al.. (2019). Baseline cfDNA characteristics and evolution of cfDNA profile during treatment with selective FGFR inhibitor TAS-120.. Journal of Clinical Oncology. 37(15_suppl). 3056–3056. 6 indexed citations
3.
Moss, Tyler J., Yuan Qi, Xi Liu, et al.. (2017). Comprehensive Genomic Characterization of Upper Tract Urothelial Carcinoma. European Urology. 72(4). 641–649. 143 indexed citations
4.
Chang, Jeffrey T., Ken Chen, Tyler J. Moss, et al.. (2017). Whole exome sequencing of metaplastic breast cancer (MpBC): Effect of mutation status on survival.. Journal of Clinical Oncology. 35(15_suppl). 1090–1090. 3 indexed citations
5.
Amir, Sumaira, Catalina Simion, Sheryl R. Krig, et al.. (2016). Regulation of the T-box transcription factor Tbx3 by the tumour suppressor microRNA-206 in breast cancer. British Journal of Cancer. 114(10). 1125–1134. 34 indexed citations
6.
Zhao, Hongyun, Lifeng Yang, Joelle Baddour, et al.. (2016). Tumor microenvironment derived exosomes pleiotropically modulate cancer cell metabolism. eLife. 5. e10250–e10250. 729 indexed citations breakdown →
7.
Moss, Tyler J., Elena G. Seviour, Vasudha Sehgal, et al.. (2015). Genome-wide perturbations by miRNAs map onto functional cellular pathways, identifying regulators of chromatin modifiers. npj Systems Biology and Applications. 1(1). 15001–15001. 5 indexed citations
8.
Faust, Joseph E., Tanvi Desai, Avani Verma, et al.. (2015). The Atlastin C-terminal Tail Is an Amphipathic Helix That Perturbs the Bilayer Structure during Endoplasmic Reticulum Homotypic Fusion. Journal of Biological Chemistry. 290(8). 4772–4783. 43 indexed citations
9.
Sehgal, Vasudha, Elena G. Seviour, Tyler J. Moss, et al.. (2015). Robust Selection Algorithm (RSA) for Multi-Omic Biomarker Discovery; Integration with Functional Network Analysis to Identify miRNA Regulated Pathways in Multiple Cancers. PLoS ONE. 10(10). e0140072–e0140072. 7 indexed citations
10.
Yang, Lifeng, Tyler J. Moss, Lingegowda S. Mangala, et al.. (2014). Metabolic shifts toward glutamine regulate tumor growth, invasion and bioenergetics in ovarian cancer. Molecular Systems Biology. 10(5). 728–728. 255 indexed citations
11.
Nishikawa, Taichiro, Nadège Bellancé, Bing Han, et al.. (2014). A switch in the source of ATP production and a loss in capacity to perform glycolysis are hallmarks of hepatocyte failure in advance liver disease. Journal of Hepatology. 60(6). 1203–1211. 97 indexed citations
12.
Chiu, Hua‐Sheng, David Llobet‐Navàs, Xuerui Yang, et al.. (2014). Cupid: simultaneous reconstruction of microRNA-target and ceRNA networks. Genome Research. 25(2). 257–267. 88 indexed citations
13.
Yang, Lifeng, Tyler J. Moss, Juan C. Marini, et al.. (2014). Abstract 3377: Glutamine mediated aggressiveness and drug sensitivity in ovarian cancer cells. Cancer Research. 74(19_Supplement). 3377–3377. 1 indexed citations
14.
Komurov, Kakajan, Melissa Muller, Elena G. Seviour, et al.. (2012). The glucose‐deprivation network counteracts lapatinib‐induced toxicity in resistant ErbB2‐positive breast cancer cells. Molecular Systems Biology. 8(1). 596–596. 92 indexed citations
15.
Nair, Usha, Jiefei Geng, Noor Gammoh, et al.. (2011). SNARE Proteins Are Required for Macroautophagy. Cell. 146(2). 290–302. 356 indexed citations
16.
Moss, Tyler J., Andrea Daga, & James A. McNew. (2011). Fusing a lasting relationship between ER tubules. Trends in Cell Biology. 21(7). 416–423. 28 indexed citations
17.
Stefano, Giovanni, Luciana Renna, Tyler J. Moss, James A. McNew, & Federica Brandizzí. (2011). In Arabidopsis, the spatial and dynamic organization of the endoplasmic reticulum and Golgi apparatus is influenced by the integrity of the C‐terminal domain of RHD3, a non‐essential GTPase. The Plant Journal. 69(6). 957–966. 54 indexed citations
18.
Moss, Tyler J., et al.. (2011). Membrane fusion by the GTPase atlastin requires a conserved C-terminal cytoplasmic tail and dimerization through the middle domain. Proceedings of the National Academy of Sciences. 108(27). 11133–11138. 60 indexed citations
19.
Pendin, Diana, et al.. (2011). GTP-dependent packing of a three-helix bundle is required for atlastin-mediated fusion. Proceedings of the National Academy of Sciences. 108(39). 16283–16288. 28 indexed citations
20.
Orso, Genny, Diana Pendin, Song Liu, et al.. (2009). Homotypic fusion of ER membranes requires the dynamin-like GTPase Atlastin. Nature. 460(7258). 978–983. 364 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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