Emily S. Sena

34.0k total citations · 6 hit papers
111 papers, 11.7k citations indexed

About

Emily S. Sena is a scholar working on Small Animals, Statistics, Probability and Uncertainty and Molecular Biology. According to data from OpenAlex, Emily S. Sena has authored 111 papers receiving a total of 11.7k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Small Animals, 25 papers in Statistics, Probability and Uncertainty and 24 papers in Molecular Biology. Recurrent topics in Emily S. Sena's work include Animal testing and alternatives (43 papers), Meta-analysis and systematic reviews (25 papers) and Acute Ischemic Stroke Management (15 papers). Emily S. Sena is often cited by papers focused on Animal testing and alternatives (43 papers), Meta-analysis and systematic reviews (25 papers) and Acute Ischemic Stroke Management (15 papers). Emily S. Sena collaborates with scholars based in United Kingdom, Australia and Netherlands. Emily S. Sena's co-authors include Malcolm Macleod, David W. Howells, Gillian L. Currie, H. Bart van der Worp, Victoria O’Collins, Lesley Colvin, Marie Fallon, H. Bart van der Worp, H. M. Vesterinen and Geoffrey A. Donnan and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American College of Cardiology and PLoS ONE.

In The Last Decade

Emily S. Sena

108 papers receiving 11.4k citations

Hit Papers

5 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.

Pharmacotherapy for neuropathic pain in adults: a systematic review and meta-analysis

2015 2.6k citations Nanna Brix Finnerup, Nadine Attal et al. The Lancet Neurology profile →
Incidence, prevalence, and predictors of chemotherapy-induced peripheral neuropathy: A systematic review and meta-analysis

2014 1.1k citations Marta Seretny, Gillian L. Currie et al. Pain profile →
Can Animal Models of Disease Reliably Inform Human Studies?

2010 900 citations H. Bart van der Worp, David W. Howells et al. profile →
Comparison of treatment effects between animal experiments and clinical trials: systematic review

2006 562 citations Emily S. Sena, Malcolm Macleod et al. profile →
Publication Bias in Reports of Animal Stroke Studies Leads to Major Overstatement of Efficacy

2010 405 citations Emily S. Sena, H. Bart van der Worp et al. profile →
Meta-analysis of data from animal studies: A practical guide

2013 374 citations H. M. Vesterinen, Emily S. Sena et al. profile →

Peers

Countries citing papers authored by Emily S. Sena

Since Specialization

Citations

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

Fields of papers citing papers by Emily S. Sena

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Emily S. Sena

This figure shows the co-authorship network connecting the top 25 collaborators of Emily S. Sena. A scholar is included among the top collaborators of Emily S. Sena 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 Emily S. Sena. Emily S. Sena 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

#	Work	Indexed citations
1	A machine learning–assisted systematic review of preclinical glioma modeling: Is practice changing with the times? 2024 ·Neuro-Oncology Advances ·Theodore C. Hirst, (unknown), (unknown), Emily S. Sena	1
2	Timing of SMN replacement therapies in mouse models of spinal muscular atrophy: a systematic review and meta-analysis 2024 ·Brain Communications ·Helena Chaytow, (unknown), Yu-Ting Huang, (unknown), Gillian L. Currie, Zsanett Bahor, Emily S. Sena, Thomas H. Gillingwater	4
3	Designing, conducting, and reporting reproducible animal experiments 2023 ·Journal of Endocrinology ·(unknown), (unknown), Kimberley E. Wever, Emily S. Sena, Malcolm Macleod, Gillian L. Currie	13
4	Screening for in vitro systematic reviews: a comparison of screening methods and training of a machine learning classifier 2023 ·Clinical Science ·(unknown), (unknown), (unknown), Joly Ghanawi, Sarah McCann, Paul M. Brennan, Jing Liao, Emily S. Sena, Malcolm Macleod	10
5	The Automated Systematic Search Deduplicator (ASySD): a rapid, open-source, interoperable tool to remove duplicate citations in biomedical systematic reviews 2023 ·BMC Biology ·Kaitlyn Hair, Zsanett Bahor, Malcolm Macleod, Jing Liao, Emily S. Sena	29
6	Synaptic dysfunction and memory impairments in transgenic Alzheimer’s disease models: A systematic review 2020 ·OSF Preprints (OSF Preprints) ·Kaitlyn Hair, Emily S. Sena, (unknown)	1
7	The open field test protocol in transgenic Alzheimer’s disease models: A systematic review 2020 ·OSF Preprints (OSF Preprints) ·Kaitlyn Hair, Emily S. Sena	1
8	From a mouse: systematic analysis reveals limitations of experiments testing interventions in Alzheimer's disease mouse models 2016 ·PubMed ·Kieren Egan, H. M. Vesterinen, (unknown), Emily S. Sena, Malcolm Macleod	30
9	Pharmacotherapy for neuropathic pain in adults: a systematic review and meta-analysis breakdown → 2015 ·The Lancet Neurology ·Nanna Brix Finnerup, Nadine Attal, Simon Haroutounian, Ewan D McNicol, Ralf Baron, Robert H. Dworkin, Ian Gilron, Maija Haanpää, Per Hansson, Troels S. Jensen, Peter Kamerman, Karen Lund, Andrew Moore, Srinivasa N. Raja, Andrew S.C. Rice, Michael C. Rowbotham, Emily S. Sena, Philip J. Siddall, Blair H. Smith, Mark S. Wallace	2620
10	Effects of MVA85A vaccine on tuberculosis challenge in animals: systematic review 2015 ·International Journal of Epidemiology ·(unknown), Emily S. Sena, Taryn Young, Paul Garner	30
11	Translational failure of anti-inflammatory compounds for myocardial infarction: a meta-analysis of large animal models 2015 ·Cardiovascular Research ·Gerardus P. J. van Hout, Sanne J. Jansen of Lorkeers, Kimberley E. Wever, Emily S. Sena, (unknown), Wouter W. van Solinge, Malcolm Macleod, Pieter A. Doevendans, Gerard Pasterkamp, Steven A. J. Chamuleau, Imo E. Hoefer	21
12	Similar effect of autologous and allogeneic cell therapy for ischaemic heart disease: systematic review and meta-analysis of large animal studies 2014 ·European Journal of Clinical Investigation ·(unknown), T. I. G. van der Spoel, H. M. Vesterinen, Emily S. Sena, Henricus J. Duckers, (unknown), Malcolm Macleod, Steven A. J. Chamuleau	1
13	Systematic Reviews and Meta-Analysis of Preclinical Studies: Why Perform Them and How to Appraise Them Critically 2014 ·Journal of Cerebral Blood Flow & Metabolism ·Emily S. Sena, Gillian L. Currie, Sarah McCann, Malcolm Macleod, David W. Howells	190
14	Incidence, prevalence, and predictors of chemotherapy-induced peripheral neuropathy: A systematic review and meta-analysis breakdown → 2014 ·Pain ·Marta Seretny, Gillian L. Currie, Emily S. Sena, Sabrina Ramnarine, Robin Grant, Malcolm Macleod, Lesley Colvin, Marie Fallon	1058
15	Transparency in the reporting of in vivo pre-clinical pain research: The relevance and implications of the ARRIVE (Animal Research: Reporting In Vivo Experiments) guidelines 2013 ·Scandinavian Journal of Pain ·Andrew S.C. Rice, (unknown), Wenlong Huang, Gillian L. Currie, Emily S. Sena, Malcolm Macleod	23
16	Systematic Review and Meta-Analysis of Therapeutic Hypothermia in Animal Models of Spinal Cord Injury 2013 ·PLoS ONE ·Peter Batchelor, Peta Skeers, Ana Antonic‐Baker, Taryn E. Wills, David W. Howells, Malcolm Macleod, Emily S. Sena	40
17	Systematic review and meta-analysis of temozolomide in animal models of glioma: was clinical efficacy predicted? 2013 ·British Journal of Cancer ·Theodore C. Hirst, H. M. Vesterinen, Emily S. Sena, Kieren Egan, Malcolm Macleod, Ian R. Whittle	79
18	Developing our understanding of the pathogenesis of Alzheimer's disease using a systematically identified dataset of interventions tested in transgenic mouse models 2012 ·European Journal of Neurology ·Kieren Egan, Emily S. Sena, H. M. Vesterinen, Malcolm Macleod	2
19	Reprint: Good laboratory practice: preventing introduction of bias at the bench (vol 29, pg 221, 2009) 2009 ·Journal of Cerebral Blood Flow & Metabolism ·Malcolm Macleod, Martin Fisher, Victoria O’Collins, Emily S. Sena, Ulrich Dirnagl, (unknown), Alastair M. Buchan, H. Bart van der Worp, Richard J. Traystman, (unknown), Geoffrey A. Donnan, David W. Howells	1
20	Good Laboratory Practice 2008 ·Stroke ·Malcolm Macleod, Marc Fisher, Victoria O’Collins, Emily S. Sena, Ulrich Dirnagl, Philip M. Bath, Alastair M. Buchan, H. Bart van der Worp, Richard J. Traystman, Kazuo Minematsu, Geoffrey A. Donnan, David W. Howells	236

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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