Tyler Weirick

996 total citations
19 papers, 691 citations indexed

About

Tyler Weirick is a scholar working on Molecular Biology, Cancer Research and Plant Science. According to data from OpenAlex, Tyler Weirick has authored 19 papers receiving a total of 691 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 9 papers in Cancer Research and 3 papers in Plant Science. Recurrent topics in Tyler Weirick's work include RNA modifications and cancer (10 papers), Cancer-related molecular mechanisms research (9 papers) and RNA Research and Splicing (5 papers). Tyler Weirick is often cited by papers focused on RNA modifications and cancer (10 papers), Cancer-related molecular mechanisms research (9 papers) and RNA Research and Splicing (5 papers). Tyler Weirick collaborates with scholars based in United States, Germany and Japan. Tyler Weirick's co-authors include Shizuka Uchida, Stefanie Dimmeler, David John, Giuseppe Militello, Claudia Döring, Rakesh Kaundal, Sitanshu Sekhar Sahu, Yuliya Ponomareva, Joseph B. Moore and Marcin Wysoczynski and has published in prestigious journals such as Bioinformatics, Circulation Research and Scientific Reports.

In The Last Decade

Tyler Weirick

19 papers receiving 688 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tyler Weirick United States 14 583 439 52 29 28 19 691
Daniel T. Youmans United States 6 803 1.4× 501 1.1× 66 1.3× 15 0.5× 39 1.4× 7 936
Xianhong Yu China 9 478 0.8× 93 0.2× 25 0.5× 17 0.6× 20 0.7× 15 526
Tao Hong China 13 388 0.7× 111 0.3× 26 0.5× 10 0.3× 18 0.6× 23 472
Eliza S. Lee Canada 8 780 1.3× 440 1.0× 55 1.1× 23 0.8× 34 1.2× 10 889
Eytan Zlotorynski United States 10 330 0.6× 131 0.3× 33 0.6× 8 0.3× 31 1.1× 117 437
Chengguo Yao China 13 937 1.6× 360 0.8× 35 0.7× 15 0.5× 18 0.6× 28 1.0k
Ramanpreet Kaur India 6 243 0.4× 230 0.5× 25 0.5× 12 0.4× 11 0.4× 9 385
Hanqing Zhao China 13 372 0.6× 139 0.3× 46 0.9× 21 0.7× 66 2.4× 23 534
Haowei Meng China 13 1.0k 1.8× 343 0.8× 106 2.0× 15 0.5× 30 1.1× 15 1.1k
Yuxi Ai United States 6 1.0k 1.7× 536 1.2× 78 1.5× 22 0.8× 10 0.4× 6 1.1k

Countries citing papers authored by Tyler Weirick

Since Specialization
Citations

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

Fields of papers citing papers by Tyler Weirick

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tyler Weirick

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

All Works

19 of 19 papers shown
1.
Guo, Yiru, Shizuka Uchida, Tyler Weirick, et al.. (2020). Administration of cardiac mesenchymal cells modulates innate immunity in the acute phase of myocardial infarction in mice. Scientific Reports. 10(1). 14754–14754. 11 indexed citations
2.
Nong, Yibing, Hong Li, Bethany W. Long, et al.. (2020). Cardiac mesenchymal cells from failing and nonfailing hearts limit ventricular dilation when administered late after infarction. American Journal of Physiology-Heart and Circulatory Physiology. 319(1). H109–H122. 9 indexed citations
3.
Moore, Joseph B., Tyler Weirick, Giuseppe Militello, et al.. (2020). The A-to-I RNA Editing Enzyme Adar1 Is Essential for Normal Embryonic Cardiac Growth and Development. Circulation Research. 127(4). 550–552. 22 indexed citations
4.
Weirick, Tyler, Giuseppe Militello, Mohammed Rabiul Hosen, et al.. (2019). Investigation of RNA Editing Sites within Bound Regions of RNA-Binding Proteins. PubMed. 8(4). 19–19. 2 indexed citations
5.
Weirick, Tyler, André Damásio, Fernando Segato, et al.. (2018). The Genome of a Thermo Tolerant, Pathogenic Albino Aspergillus fumigatus. Frontiers in Microbiology. 9. 1827–1827. 11 indexed citations
6.
Hosen, Mohammed Rabiul, Giuseppe Militello, Tyler Weirick, et al.. (2018). Airn Regulates Igf2bp2 Translation in Cardiomyocytes. Circulation Research. 122(10). 1347–1353. 31 indexed citations
7.
Militello, Giuseppe, Mohammed Rabiul Hosen, Yuliya Ponomareva, et al.. (2018). A novel long non-coding RNA Myolinc regulates myogenesis through TDP-43 and Filip1. Journal of Molecular Cell Biology. 10(2). 102–117. 52 indexed citations
8.
Weirick, Tyler, Giuseppe Militello, & Shizuka Uchida. (2018). Long Non-coding RNAs in Endothelial Biology. Frontiers in Physiology. 9(531). 91–522. 26 indexed citations
9.
Weirick, Tyler, David John, & Shizuka Uchida. (2016). Resolving the problem of multiple accessions of the same transcript deposited across various public databases. Briefings in Bioinformatics. 18(2). bbw017–bbw017. 7 indexed citations
10.
Weirick, Tyler, Giuseppe Militello, Yuliya Ponomareva, et al.. (2016). Logic programming to infer complex RNA expression patterns from RNA-seq data. Briefings in Bioinformatics. 19(2). bbw117–bbw117. 17 indexed citations
11.
Weirick, Tyler, David John, Giuseppe Militello, et al.. (2016). ANGIOGENES: knowledge database for protein-coding and noncoding RNA genes in endothelial cells. Scientific Reports. 6(1). 32475–32475. 23 indexed citations
12.
Militello, Giuseppe, Tyler Weirick, David John, et al.. (2016). Screening and validation of lncRNAs and circRNAs as miRNA sponges. Briefings in Bioinformatics. bbw053–bbw053. 280 indexed citations
13.
John, David, Tyler Weirick, Stefanie Dimmeler, & Shizuka Uchida. (2016). RNAEditor: easy detection of RNA editing events and the introduction of editing islands. Briefings in Bioinformatics. 18(6). bbw087–bbw087. 60 indexed citations
14.
Weirick, Tyler, David John, Stefanie Dimmeler, & Shizuka Uchida. (2015). C-It-Loci: a knowledge database for tissue-enriched loci. Bioinformatics. 31(21). 3537–3543. 27 indexed citations
15.
Prabhakaran, Madhu, et al.. (2015). Genome Sequences of the Lignin-Degrading Pseudomonas sp. Strain YS-1p and Rhizobium sp. Strain YS-1r Isolated from Decaying Wood. Genome Announcements. 3(2). 21 indexed citations
16.
Weirick, Tyler, et al.. (2015). The identification and characterization of novel transcripts from RNA-seq data. Briefings in Bioinformatics. 17(4). 678–685. 28 indexed citations
17.
Weirick, Tyler, Sitanshu Sekhar Sahu, Ramamurthy Mahalingam, & Rakesh Kaundal. (2014). LacSubPred: predicting subtypes of Laccases, an important lignin metabolism-related enzyme class, using in silico approaches. BMC Bioinformatics. 15(S11). S15–S15. 17 indexed citations
18.
Sahu, Sitanshu Sekhar, Tyler Weirick, & Rakesh Kaundal. (2014). Predicting genome-scale Arabidopsis-Pseudomonas syringae interactome using domain and interolog-based approaches. BMC Bioinformatics. 15(S11). S13–S13. 31 indexed citations
19.
Kaundal, Rakesh, et al.. (2013). Identification and characterization of plastid-type proteins from sequence-attributed features using machine learning. BMC Bioinformatics. 14(S14). 16 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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