Tyler S. Klann

737 total citations
9 papers, 464 citations indexed

About

Tyler S. Klann is a scholar working on Molecular Biology, Biomedical Engineering and Cellular and Molecular Neuroscience. According to data from OpenAlex, Tyler S. Klann has authored 9 papers receiving a total of 464 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 3 papers in Biomedical Engineering and 1 paper in Cellular and Molecular Neuroscience. Recurrent topics in Tyler S. Klann's work include CRISPR and Genetic Engineering (6 papers), RNA and protein synthesis mechanisms (4 papers) and Pluripotent Stem Cells Research (3 papers). Tyler S. Klann is often cited by papers focused on CRISPR and Genetic Engineering (6 papers), RNA and protein synthesis mechanisms (4 papers) and Pluripotent Stem Cells Research (3 papers). Tyler S. Klann collaborates with scholars based in United States, China and Germany. Tyler S. Klann's co-authors include Charles A. Gersbach, Joshua B. Black, Timothy E. Reddy, Gregory E. Crawford, Malathi Chellappan, Isaac B. Hilton, Alexias Safi, Lingyun Song, Alejandro Barrera and Randolph S. Ashton and has published in prestigious journals such as Nature Biotechnology, Scientific Reports and Lab on a Chip.

In The Last Decade

Tyler S. Klann

9 papers receiving 458 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tyler S. Klann United States	7	420	74	36	33	28	9	464
Jackson Winter United States	6	372 0.9×	125 1.7×	30 0.8×	15 0.5×	17 0.6×	11	419
Miaojin Zhou China	12	312 0.7×	59 0.8×	37 1.0×	18 0.5×	13 0.5×	35	379
Nathan H. Kipniss United States	4	408 1.0×	42 0.6×	79 2.2×	13 0.4×	23 0.8×	4	464
Congting Guo China	3	245 0.6×	55 0.7×	24 0.7×	13 0.4×	13 0.5×	5	306
Michaela Willi United States	12	478 1.1×	108 1.5×	18 0.5×	56 1.7×	11 0.4×	19	575
Janine Scholefield South Africa	10	302 0.7×	68 0.9×	13 0.4×	56 1.7×	14 0.5×	29	372
Cory Smith United States	9	434 1.0×	113 1.5×	23 0.6×	15 0.5×	26 0.9×	13	489
Carmen Adriaens United States	5	446 1.1×	86 1.2×	8 0.2×	49 1.5×	35 1.3×	5	495
Jiabiao Hu China	10	358 0.9×	45 0.6×	17 0.5×	31 0.9×	19 0.7×	16	412
Bingbing He China	6	484 1.2×	121 1.6×	14 0.4×	21 0.6×	17 0.6×	13	528

Countries citing papers authored by Tyler S. Klann

Since Specialization

Citations

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

Fields of papers citing papers by Tyler S. Klann

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tyler S. Klann

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

All Works

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9 of 9 papers shown

Black, Joshua B., Alejandro Barrera, Tyler S. Klann, et al.. (2020). Master Regulators and Cofactors of Human Neuronal Cell Fate Specification Identified by CRISPR Gene Activation Screens. Cell Reports. 33(9). 108460–108460. 49 indexed citations

Huang, Jianguo, Mark Chen, Eric S. Xu, et al.. (2019). Genome-wide CRISPR Screen to Identify Genes that Suppress Transformation in the Presence of Endogenous KrasG12D. Scientific Reports. 9(1). 17220–17220. 5 indexed citations

Black, Joshua B., Tyler S. Klann, Christopher E. Nelson, et al.. (2019). Targeted transcriptional modulation with type I CRISPR–Cas systems in human cells. Nature Biotechnology. 37(12). 1493–1501. 65 indexed citations

Klann, Tyler S., Joshua B. Black, & Charles A. Gersbach. (2018). CRISPR-based methods for high-throughput annotation of regulatory DNA. Current Opinion in Biotechnology. 52. 32–41. 12 indexed citations

Klann, Tyler S., Gregory E. Crawford, Timothy E. Reddy, & Charles A. Gersbach. (2018). Screening Regulatory Element Function with CRISPR/Cas9-based Epigenome Editing. Methods in molecular biology. 1767. 447–480. 6 indexed citations

Klann, Tyler S., Joshua B. Black, Malathi Chellappan, et al.. (2017). CRISPR–Cas9 epigenome editing enables high-throughput screening for functional regulatory elements in the human genome. Nature Biotechnology. 35(6). 561–568. 285 indexed citations

Prestil, Ryan, et al.. (2015). High‐content imaging with micropatterned multiwell plates reveals influence of cell geometry and cytoskeleton on chromatin dynamics. Biotechnology Journal. 10(10). 1555–1567. 20 indexed citations

Klann, Tyler S., Sha Jin, Max R. Salick, et al.. (2014). High-precision robotic microcontact printing (R-μCP) utilizing a vision guided selectively compliant articulated robotic arm. Lab on a Chip. 14(11). 1923–1923. 15 indexed citations

Knight, Gavin, et al.. (2014). Fabricating Complex Culture Substrates Using Robotic Microcontact Printing (R-µCP) and Sequential Nucleophilic Substitution. Journal of Visualized Experiments. e52186–e52186. 7 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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