Toby Dylan Hocking

3.7k total citations · 1 hit paper
33 papers, 1.2k citations indexed

About

Toby Dylan Hocking is a scholar working on Molecular Biology, Artificial Intelligence and Genetics. According to data from OpenAlex, Toby Dylan Hocking has authored 33 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 6 papers in Artificial Intelligence and 6 papers in Genetics. Recurrent topics in Toby Dylan Hocking's work include Gene expression and cancer classification (6 papers), Genomics and Chromatin Dynamics (4 papers) and Statistical Methods and Inference (4 papers). Toby Dylan Hocking is often cited by papers focused on Gene expression and cancer classification (6 papers), Genomics and Chromatin Dynamics (4 papers) and Statistical Methods and Inference (4 papers). Toby Dylan Hocking collaborates with scholars based in United States, Canada and France. Toby Dylan Hocking's co-authors include George E. Katibah, Jasmine M. McCammon, Catherine Ngo, Sharon L. Amacher, Lei Zhang, Jeffrey C. Miller, Fyodor D. Urnov, Yannick Doyon, Edward J. Rebar and Philip D. Gregory and has published in prestigious journals such as Nature Biotechnology, Bioinformatics and PLoS ONE.

In The Last Decade

Toby Dylan Hocking

28 papers receiving 1.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Heritable targeted gene disruption in zebrafish using designed zinc-finger nucleases

2008 681 citations Yannick Doyon, Jasmine M. McCammon et al. Nature Biotechnology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Toby Dylan Hocking United States	13	782	323	189	96	79	33	1.2k
Juan L. Mateo Spain	13	1.1k 1.4×	230 0.7×	86 0.5×	212 2.2×	132 1.7×	29	1.6k
Keith A. Boroevich Japan	21	1.0k 1.3×	746 2.3×	211 1.1×	76 0.8×	154 1.9×	38	1.8k
Ramana M. Idury United States	11	833 1.1×	617 1.9×	94 0.5×	123 1.3×	188 2.4×	15	1.7k
Ronald Richman South Africa	22	1.6k 2.1×	838 2.6×	198 1.0×	64 0.7×	96 1.2×	64	2.5k
Lei M. Li United States	14	699 0.9×	578 1.8×	58 0.3×	95 1.0×	22 0.3×	47	1.3k
Szabolcs Szelinger United States	15	499 0.6×	490 1.5×	45 0.2×	69 0.7×	373 4.7×	26	1.3k
Dongxiao Zhu United States	22	1.2k 1.5×	107 0.3×	125 0.7×	183 1.9×	353 4.5×	101	2.1k
Leila Mureşan United Kingdom	18	906 1.2×	124 0.4×	195 1.0×	57 0.6×	40 0.5×	47	1.3k
Florian Hahne United States	10	1.1k 1.5×	201 0.6×	38 0.2×	112 1.2×	57 0.7×	17	1.6k
Seth Falcon United States	8	1.2k 1.6×	282 0.9×	54 0.3×	200 2.1×	65 0.8×	14	2.2k

Countries citing papers authored by Toby Dylan Hocking

Since Specialization

Citations

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

Fields of papers citing papers by Toby Dylan Hocking

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Toby Dylan Hocking. 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 Toby Dylan Hocking. The network helps show where Toby Dylan Hocking may publish in the future.

Co-authorship network of co-authors of Toby Dylan Hocking

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

All Works

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20 of 20 papers shown

Propster, Jeffrey, et al.. (2025). Cross-validation for training and testing co-occurrence network inference algorithms. BMC Bioinformatics. 26(1). 74–74.

Buscombe, Daniel, et al.. (2024). Automated River Substrate Mapping From Sonar Imagery With Machine Learning. 1(3). 2 indexed citations

Hocking, Toby Dylan, et al.. (2023). gfpop: An R Package for Univariate Graph-Constrained Change-Point Detection. Journal of Statistical Software. 106(6). 3 indexed citations

Hocking, Toby Dylan, et al.. (2023). Predicting Neuromuscular Engagement to Improve Gait Training With a Robotic Ankle Exoskeleton. IEEE Robotics and Automation Letters. 8(8). 5055–5060. 13 indexed citations

Mihaljevic, Joseph R., et al.. (2022). SPARSEMODr: Rapidly simulate spatially explicit and stochastic models of COVID-19 and other infectious diseases. Biology Methods and Protocols. 7(1). bpac022–bpac022. 2 indexed citations

Shaw, Peter, et al.. (2022). Graph Embedding: A Methodological Survey. 142–148. 2 indexed citations

Hocking, Toby Dylan, et al.. (2022). Labeled optimal partitioning. Computational Statistics. 38(1). 461–480. 2 indexed citations

Rigaill, Guillem, et al.. (2021). Increased peak detection accuracy in over-dispersed ChIP-seq data with supervised segmentation models. BMC Bioinformatics. 22(1). 323–323. 3 indexed citations

Hocking, Toby Dylan, et al.. (2021). Linear Time Dynamic Programming for Computing Breakpoints in the Regularization Path of Models Selected From a Finite Set. Journal of Computational and Graphical Statistics. 31(2). 313–323.

10.

Hocking, Toby Dylan, et al.. (2021). A greedy graph search algorithm based on changepoint analysis for automatic QRS complex detection. Computers in Biology and Medicine. 130. 104208–104208. 7 indexed citations

11.

Sievert, Carson, et al.. (2021). Create Interactive Web Graphics via 'plotly.js' [R package plotly version 4.10.0]. 6 indexed citations

12.

Abraham, Andrew J., et al.. (2020). Improved estimation of gut passage time considerably affects trait‐based dispersal models. Functional Ecology. 35(4). 860–869. 13 indexed citations

13.

Hocking, Toby Dylan & Guillaume Bourque. (2019). Machine learning algorithms for simultaneous supervised detection of peaks in multiple samples and cell types. PubMed. 25. 367–378. 3 indexed citations

14.

Alirezaie, Najmeh, Kristin D. Kernohan, Taila Hartley, Jacek Majewski, & Toby Dylan Hocking. (2018). ClinPred: Prediction Tool to Identify Disease-Relevant Nonsynonymous Single-Nucleotide Variants. The American Journal of Human Genetics. 103(4). 474–483. 141 indexed citations

15.

Köster, Jan, Valentina Boeva, Toby Dylan Hocking, et al.. (2018). Meta-mining of copy number profiles of high-risk neuroblastoma tumors. Scientific Data. 5(1). 180240–180240. 18 indexed citations

16.

Shimada, Kazuyuki, Satoko Shimada, Keiji Sugimoto, et al.. (2016). Development and analysis of patient-derived xenograft mouse models in intravascular large B-cell lymphoma. Leukemia. 30(7). 1568–1579. 21 indexed citations

17.

Maidstone, Robert, Toby Dylan Hocking, Guillem Rigaill, & Paul Fearnhead. (2016). On optimal multiple changepoint algorithms for large data. Statistics and Computing. 27(2). 519–533. 100 indexed citations

18.

Hocking, Toby Dylan, Gudrun Schleiermacher, Isabelle Janoueix‐Lerosey, et al.. (2013). Learning smoothing models of copy number profiles using breakpoint annotations. BMC Bioinformatics. 14(1). 164–164. 27 indexed citations

19.

Gautier, Mathieu, Toby Dylan Hocking, & Jean‐Louis Foulley. (2010). A Bayesian Outlier Criterion to Detect SNPs under Selection in Large Data Sets. PLoS ONE. 5(8). e11913–e11913. 14 indexed citations

20.

Doyon, Yannick, Jasmine M. McCammon, Jeffrey C. Miller, et al.. (2008). Heritable targeted gene disruption in zebrafish using designed zinc-finger nucleases. Nature Biotechnology. 26(6). 702–708. 681 indexed citations breakdown →

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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