Mark W. Kankel

3.5k total citations · 2 hit papers
18 papers, 2.4k citations indexed

About

Mark W. Kankel is a scholar working on Molecular Biology, Neurology and Genetics. According to data from OpenAlex, Mark W. Kankel has authored 18 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 7 papers in Neurology and 4 papers in Genetics. Recurrent topics in Mark W. Kankel's work include Amyotrophic Lateral Sclerosis Research (7 papers), Developmental Biology and Gene Regulation (5 papers) and Neurogenetic and Muscular Disorders Research (4 papers). Mark W. Kankel is often cited by papers focused on Amyotrophic Lateral Sclerosis Research (7 papers), Developmental Biology and Gene Regulation (5 papers) and Neurogenetic and Muscular Disorders Research (4 papers). Mark W. Kankel collaborates with scholars based in United States, France and Singapore. Mark W. Kankel's co-authors include Spyros Artavanis‐Tsakonas, K. G. Guruharsha, Gregory D Hurlbut, Anindya Sen, Jeremy R. Haag, Eric J. Richards, Douglas E. Ramsey, Susan K. Flowers, Nicole C. Riddle and Trevor Stokes and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Mark W. Kankel

18 papers receiving 2.4k citations

Hit Papers

Context-Dependent and Disease-Specific Diversity ... 2012 2026 2016 2021 2018 2012 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mark W. Kankel United States 16 1.8k 488 310 281 273 18 2.4k
Lance S. Davidow United States 23 2.8k 1.5× 349 0.7× 262 0.8× 167 0.6× 312 1.1× 37 3.4k
Kasey R. Hutt United States 12 2.4k 1.3× 225 0.5× 549 1.8× 834 3.0× 100 0.4× 17 3.0k
Lily Shiue United States 28 4.4k 2.4× 368 0.8× 682 2.2× 776 2.8× 139 0.5× 34 5.6k
Kathi Zarnack Germany 29 3.6k 2.0× 238 0.5× 101 0.3× 89 0.3× 174 0.6× 73 3.9k
Antony E. Shrimpton United States 21 842 0.5× 219 0.4× 185 0.6× 84 0.3× 334 1.2× 51 2.0k
Hairi Li United States 31 4.6k 2.6× 728 1.5× 265 0.9× 154 0.5× 1.2k 4.3× 43 5.9k
Satomi Mitsuhashi Japan 28 1.8k 1.0× 83 0.2× 299 1.0× 113 0.4× 299 1.1× 99 2.4k
Marion Leleu Switzerland 22 2.6k 1.4× 532 1.1× 48 0.2× 331 1.2× 188 0.7× 30 3.7k
Christoph S. Clemen Germany 29 1.4k 0.8× 70 0.1× 214 0.7× 147 0.5× 856 3.1× 89 2.1k
Soonmoon Yoo United States 28 1.7k 0.9× 95 0.2× 149 0.5× 126 0.4× 305 1.1× 37 2.3k

Countries citing papers authored by Mark W. Kankel

Since Specialization
Citations

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

Fields of papers citing papers by Mark W. Kankel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark W. Kankel. 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 Mark W. Kankel. The network helps show where Mark W. Kankel may publish in the future.

Co-authorship network of co-authors of Mark W. Kankel

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

All Works

18 of 18 papers shown
1.
Krishnan, Gopinath, Denitza Raitcheva, Daniel A. Bartlett, et al.. (2022). Poly(GR) and poly(GA) in cerebrospinal fluid as potential biomarkers for C9ORF72-ALS/FTD. Nature Communications. 13(1). 2799–2799. 31 indexed citations
2.
Sonobe, Yoshifumi, Gopinath Krishnan, Ghanashyam D. Ghadge, et al.. (2021). A C. elegans model of C9orf72-associated ALS/FTD uncovers a conserved role for eIF2D in RAN translation. Nature Communications. 12(1). 6025–6025. 36 indexed citations
3.
Krishnan, Gopinath, Yu Zhang, Yuanzheng Gu, et al.. (2020). CRISPR deletion of the C9ORF72 promoter in ALS/FTD patient motor neurons abolishes production of dipeptide repeat proteins and rescues neurodegeneration. Acta Neuropathologica. 140(1). 81–84. 30 indexed citations
4.
Kankel, Mark W., Anindya Sen, Lei Lü, et al.. (2020). Amyotrophic Lateral Sclerosis Modifiers inDrosophilaReveal the Phospholipase D Pathway as a Potential Therapeutic Target. Genetics. 215(3). 747–766. 22 indexed citations
5.
Sarraf, Shireen A., Dionisia P. Sideris, Νικόλαος Γιαγτζόγλου, et al.. (2019). PINK1/Parkin Influences Cell Cycle by Sequestering TBK1 at Damaged Mitochondria, Inhibiting Mitosis. Cell Reports. 29(1). 225–235.e5. 72 indexed citations
6.
Chen, Hongbo, et al.. (2018). Exploring the genetics and non-cell autonomous mechanisms underlying ALS/FTLD. Cell Death and Differentiation. 25(4). 648–662. 64 indexed citations
7.
Markmiller, Sebastian, Sahar Soltanieh, Raymond Mak, et al.. (2018). Context-Dependent and Disease-Specific Diversity in Protein Interactions within Stress Granules. Cell. 172(3). 590–604.e13. 626 indexed citations breakdown →
8.
Markmiller, Sebastian, Sahar Soltanieh, Raymond Mak, et al.. (2018). Context‐dependent and Disease‐specific Diversity in Stress Granules Formed from Pre‐existing Protein Interactions. The FASEB Journal. 32(S1). 3 indexed citations
9.
Periz, Goran, Jiayin Lu, Tao Zhang, et al.. (2015). Regulation of Protein Quality Control by UBE4B and LSD1 through p53-Mediated Transcription. PLoS Biology. 13(4). e1002114–e1002114. 36 indexed citations
10.
Sen, Anindya, K. G. Guruharsha, Mark W. Kankel, et al.. (2013). Genetic circuitry of Survival motor neuron , the gene underlying spinal muscular atrophy. Proceedings of the National Academy of Sciences. 110(26). E2371–80. 29 indexed citations
11.
Guruharsha, K. G., Mark W. Kankel, & Spyros Artavanis‐Tsakonas. (2012). The Notch signalling system: recent insights into the complexity of a conserved pathway. Nature Reviews Genetics. 13(9). 654–666. 546 indexed citations breakdown →
12.
Sen, Anindya, Takakazu Yokokura, Mark W. Kankel, et al.. (2011). Modeling spinal muscular atrophy in Drosophila links Smn to FGF signaling. The Journal of Cell Biology. 192(3). 481–495. 39 indexed citations
13.
Hurlbut, Gregory D, Mark W. Kankel, & Spyros Artavanis‐Tsakonas. (2009). Nodal points and complexity of Notch-Ras signal integration. Proceedings of the National Academy of Sciences. 106(7). 2218–2223. 31 indexed citations
14.
Chang, Howard C., Takakazu Yokokura, Ashim Mukherjee, et al.. (2008). Modeling Spinal Muscular Atrophy in Drosophila. PLoS ONE. 3(9). e3209–e3209. 139 indexed citations
15.
Hurlbut, Gregory D, Mark W. Kankel, Robert J. Lake, & Spyros Artavanis‐Tsakonas. (2007). Crossing paths with Notch in the hyper-network. Current Opinion in Cell Biology. 19(2). 166–175. 194 indexed citations
16.
Kankel, Mark W., Gregory D Hurlbut, Geeta Upadhyay, et al.. (2007). Investigating the Genetic Circuitry of Mastermind in Drosophila, a Notch Signal Effector. Genetics. 177(4). 2493–2505. 57 indexed citations
17.
Kankel, Mark W., Dianne Duncan, & Ian Duncan. (2004). A Screen for Genes That Interact With the Drosophila Pair-Rule Segmentation Gene fushi tarazu. Genetics. 168(1). 161–180. 15 indexed citations
18.
Kankel, Mark W., Douglas E. Ramsey, Trevor Stokes, et al.. (2003). Arabidopsis MET1 Cytosine Methyltransferase Mutants. Genetics. 163(3). 1109–1122. 471 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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