Daniel J. Lavery

2.8k total citations
38 papers, 1.6k citations indexed

About

Daniel J. Lavery is a scholar working on Molecular Biology, Hardware and Architecture and Cellular and Molecular Neuroscience. According to data from OpenAlex, Daniel J. Lavery has authored 38 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 14 papers in Hardware and Architecture and 10 papers in Cellular and Molecular Neuroscience. Recurrent topics in Daniel J. Lavery's work include Parallel Computing and Optimization Techniques (14 papers), Embedded Systems Design Techniques (7 papers) and Mitochondrial Function and Pathology (5 papers). Daniel J. Lavery is often cited by papers focused on Parallel Computing and Optimization Techniques (14 papers), Embedded Systems Design Techniques (7 papers) and Mitochondrial Function and Pathology (5 papers). Daniel J. Lavery collaborates with scholars based in United States, Switzerland and Germany. Daniel J. Lavery's co-authors include Ueli Schibler, John Paul Shen, Hong Wang, Jamison D. Collins, Dean M. Tullsen, Yong-Fong Lee, Christopher J. Hughes, Selina Chen‐Kiang, Étienne Audinat and Fabienne Fleury-Olela and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Genes & Development.

In The Last Decade

Daniel J. Lavery

38 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel J. Lavery United States 17 499 497 415 360 255 38 1.6k
John Boyle United States 18 203 0.4× 667 1.3× 228 0.5× 115 0.3× 52 0.2× 51 1.4k
Andrew S. Yoo United States 28 83 0.2× 2.9k 5.8× 134 0.3× 878 2.4× 80 0.3× 48 3.8k
Guohua Jin China 24 163 0.3× 850 1.7× 158 0.4× 288 0.8× 15 0.1× 112 1.8k
Andrew Kennedy United States 24 145 0.3× 603 1.2× 78 0.2× 120 0.3× 36 0.1× 61 1.4k
Krishnan Padmanabhan United States 19 128 0.3× 325 0.7× 446 1.1× 430 1.2× 10 0.0× 82 1.8k
Christina Patrick United States 31 47 0.1× 1.4k 2.9× 107 0.3× 1.7k 4.7× 34 0.1× 47 5.0k
Junko Takahashi Japan 20 102 0.2× 322 0.6× 27 0.1× 369 1.0× 27 0.1× 62 1.9k
Takeshi Yoshimura Japan 20 66 0.1× 1.3k 2.6× 35 0.1× 1.2k 3.3× 19 0.1× 64 2.5k
David T. Liu Austria 21 27 0.1× 786 1.6× 204 0.5× 600 1.7× 18 0.1× 91 2.3k

Countries citing papers authored by Daniel J. Lavery

Since Specialization
Citations

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

Fields of papers citing papers by Daniel J. Lavery

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel J. Lavery

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel J. Lavery. A scholar is included among the top collaborators of Daniel J. Lavery 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 Daniel J. Lavery. Daniel J. Lavery 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.
Neueder, Andreas, Kerstin Kojer, Daniel J. Lavery, et al.. (2022). Abnormal molecular signatures of inflammation, energy metabolism, and vesicle biology in human Huntington disease peripheral tissues. Genome biology. 23(1). 189–189. 10 indexed citations
2.
Chen, Teresa C., Elizabeth D. Buttermore, Robin J. Kleiman, et al.. (2021). Generation and characterization of human induced pluripotent stem cells (iPSCs) from three male and three female patients with CDKL5 Deficiency Disorder (CDD). Stem Cell Research. 53. 102276–102276. 7 indexed citations
3.
Ghavami, Afshin, Michael Olsen, Mei Kwan, et al.. (2020). Transcriptional Assessment of Striatal mRNAs as Valid Biomarkers of Disease Progression in Three Mouse Models of Huntington’s Disease. Journal of Huntington s Disease. 9(1). 13–31. 2 indexed citations
4.
Cariulo, Cristina, Margherita Verani, Raffaele Ingenito, et al.. (2019). Ultrasensitive quantitative measurement of huntingtin phosphorylation at residue S13. Biochemical and Biophysical Research Communications. 521(3). 549–554. 10 indexed citations
5.
Arbez, Nicolas, Tamara Ratovitski, Ekaterine Chighladze, et al.. (2017). Post-translational modifications clustering within proteolytic domains decrease mutant huntingtin toxicity. Journal of Biological Chemistry. 292(47). 19238–19249. 44 indexed citations
6.
Levin, Margaret, Jason Jin, Rui‐Ru Ji, et al.. (2007). Complement activation in the peripheral nervous system following the spinal nerve ligation model of neuropathic pain ☆. Pain. 137(1). 182–201. 74 indexed citations
7.
Pruthi, Farhana, Xuesong Liu, Rok Cerne, et al.. (2006). Pharmacological characterization of recombinant N-type calcium channel (Cav2.2) mediated calcium mobilization using FLIPR. Biochemical Pharmacology. 72(6). 770–782. 26 indexed citations
8.
Doerflinger, Nathalie, et al.. (2005). Two Populations of Layer V Pyramidal Cells of the Mouse Neocortex: Development and Sensitivity to Anesthetics. Journal of Neurophysiology. 94(5). 3357–3367. 72 indexed citations
9.
10.
Lavery, Daniel J., Philippe Fonjallaz, Fabienne Fleury-Olela, & Ueli Schibler. (2003). Analysis of Differential Gene Expression Using the SABRE Enrichment Protocol. Humana Press eBooks. 99. 321–345. 1 indexed citations
11.
Collard⋆, Jean-François & Daniel J. Lavery. (2003). Optimizations to prevent cache penalties for the Intel/spl reg/ Itanium/spl reg/ 2 processor. 105–114. 3 indexed citations
12.
Wang, Perry H., et al.. (2002). Post-pass binary adaptation for software-based speculative precomputation. 6 indexed citations
13.
Staiger, Jochen F., et al.. (2002). Two Types of Nicotinic Receptors Mediate an Excitation of Neocortical Layer I Interneurons. Journal of Neurophysiology. 88(3). 1318–1327. 113 indexed citations
14.
Wang, Perry H., et al.. (2002). Post-pass binary adaptation for software-based speculative precomputation. 117–128. 75 indexed citations
15.
16.
Ghiya, Rakesh, Daniel J. Lavery, & David Sehr. (2001). On the importance of points-to analysis and other memory disambiguation methods for C programs. 47–58. 71 indexed citations
17.
Lavery, Daniel J. & Ueli Schibler. (1993). Circadian transcription of the cholesterol 7 alpha hydroxylase gene may involve the liver-enriched bZIP protein DBP.. Genes & Development. 7(10). 1871–1884. 268 indexed citations
18.
Chen‐Kiang, Selina & Daniel J. Lavery. (1989). [7] Preparation of precursors to mRNA from mammalian cell nuclei. Methods in enzymology on CD-ROM/Methods in enzymology. 180. 69–82. 15 indexed citations
19.
Chen‐Kiang, Selina & Daniel J. Lavery. (1989). [8] Pulse labeling of heterogeneous nuclear RNA in isolated nuclei. Methods in enzymology on CD-ROM/Methods in enzymology. 180. 82–96. 19 indexed citations
20.
Lavery, Daniel J. & Sanjeev Saksena. (1987). Management of refractory sustained ventricular tachycardia with amiodarone: A reappraisal. American Heart Journal. 113(1). 49–56. 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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