Ralph E. Leighty

474 total citations
10 papers, 365 citations indexed

About

Ralph E. Leighty is a scholar working on Molecular Biology, Computational Theory and Mathematics and Physiology. According to data from OpenAlex, Ralph E. Leighty has authored 10 papers receiving a total of 365 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 5 papers in Computational Theory and Mathematics and 5 papers in Physiology. Recurrent topics in Ralph E. Leighty's work include Alzheimer's disease research and treatments (5 papers), Computational Drug Discovery Methods (5 papers) and Gene expression and cancer classification (2 papers). Ralph E. Leighty is often cited by papers focused on Alzheimer's disease research and treatments (5 papers), Computational Drug Discovery Methods (5 papers) and Gene expression and cancer classification (2 papers). Ralph E. Leighty collaborates with scholars based in United States. Ralph E. Leighty's co-authors include Gary W. Arendash, Jennifer R. Cracchiolo, Maren Jensen, Huntington Potter, Marcos F Garcia, Mike Hutton, Jada Lewis, Eileen McGowan, N. Salem and Nahed Hussein and has published in prestigious journals such as Nucleic Acids Research, Brain Research and Neuroscience.

In The Last Decade

Ralph E. Leighty

10 papers receiving 355 citations

Peers

Ralph E. Leighty

PHYSI

CMN

NEURO

Kathryn J. Bryan United States

Cristiane Batassini Brazil

Krishna Bharani United States

Nasrin Hashemi-Firouzi Iran

Diana Thyssen United States

Norimichi Nakamura Japan

Felipe C. Ribeiro Brazil

Ivica Granic Netherlands

Roger Lefort United States

André Vernay Switzerland

Kathryn J. Bryan United States

Ralph E. Leighty

191 ×0.8

PHYSI

77 ×0.8

69 ×0.9

CMN

67 ×0.9

NEURO

70 ×1.3

Citations per year, relative to Ralph E. Leighty Ralph E. Leighty (= 1×) peers Kathryn J. Bryan

Countries citing papers authored by Ralph E. Leighty

Since Specialization

Citations

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

Fields of papers citing papers by Ralph E. Leighty

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ralph E. Leighty. 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 Ralph E. Leighty. The network helps show where Ralph E. Leighty may publish in the future.

Co-authorship network of co-authors of Ralph E. Leighty

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

All Works

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10 of 10 papers shown

Varma, Sameer, et al.. (2014). Discerning intersecting fusion‐activation pathways in the Nipah virus using machine learning. Proteins Structure Function and Bioinformatics. 82(12). 3241–3254. 8 indexed citations

Leighty, Ralph E., et al.. (2012). Duplicate gene enrichment and expression pattern diversification in multicellularity. Nucleic Acids Research. 40(16). 7597–7605. 8 indexed citations

Leighty, Ralph E. & Sameer Varma. (2012). Quantifying Changes in Intrinsic Molecular Motion Using Support Vector Machines. Journal of Chemical Theory and Computation. 9(2). 868–875. 9 indexed citations

Leighty, Ralph E.. (2009). Statistical and Data Mining Methodologies for Behavioral Analysis in Transgenic Mouse Models of Alzheimer’s Disease: Parallels with Human AD Evaluation. Digital Commons - University of South Florida (University of South Florida). 1 indexed citations

Arendash, Gary W., Maren Jensen, N. Salem, et al.. (2007). A diet high in omega-3 fatty acids does not improve or protect cognitive performance in Alzheimer’s transgenic mice. Neuroscience. 149(2). 286–302. 84 indexed citations

Leighty, Ralph E., Melissa Runfeldt, Donald J. Berndt, et al.. (2007). Use of artificial neural networks to determine cognitive impairment and therapeutic effectiveness in Alzheimer's transgenic mice. Journal of Neuroscience Methods. 167(2). 358–366. 6 indexed citations

Leighty, Ralph E., Lars Nilsson, Huntington Potter, et al.. (2004). Use of multimetric statistical analysis to characterize and discriminate between the performance of four Alzheimer’s transgenic mouse lines differing in Aβ deposition. Behavioural Brain Research. 153(1). 107–121. 40 indexed citations

Arendash, Gary W., Jada Lewis, Ralph E. Leighty, et al.. (2004). Multi-metric behavioral comparison of APPsw and P301L models for Alzheimer's Disease: linkage of poorer cognitive performance to tau pathology in forebrain. Brain Research. 1012(1-2). 29–41. 97 indexed citations

Jensen, Maren, Melina Mottin, Jennifer R. Cracchiolo, Ralph E. Leighty, & Gary W. Arendash. (2004). Lifelong immunization with human β-amyloid (1–42) protects Alzheimer's transgenic mice against cognitive impairment throughout aging. Neuroscience. 130(3). 667–684. 52 indexed citations

10.

Nilsson, Lars, Gary W. Arendash, Ralph E. Leighty, et al.. (2004). Cognitive impairment in PDAPP mice depends on ApoE and ACT-catalyzed amyloid formation. Neurobiology of Aging. 25(9). 1153–1167. 60 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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