Roberto Puch‐Solis

618 total citations
24 papers, 416 citations indexed

About

Roberto Puch‐Solis is a scholar working on Genetics, Molecular Biology and Ecology. According to data from OpenAlex, Roberto Puch‐Solis has authored 24 papers receiving a total of 416 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Genetics, 10 papers in Molecular Biology and 3 papers in Ecology. Recurrent topics in Roberto Puch‐Solis's work include Forensic and Genetic Research (14 papers), Molecular Biology Techniques and Applications (10 papers) and Biometric Identification and Security (3 papers). Roberto Puch‐Solis is often cited by papers focused on Forensic and Genetic Research (14 papers), Molecular Biology Techniques and Applications (10 papers) and Biometric Identification and Security (3 papers). Roberto Puch‐Solis collaborates with scholars based in United Kingdom, New Zealand and India. Roberto Puch‐Solis's co-authors include James M. Curran, Cédric Neumann, Nicole Egli, Christophe Champod, Peter Gill, Susan Pope, I.W. Evett, Tim Clayton, David J. Balding and Lauren R. Rodgers and has published in prestigious journals such as Forensic Science International, Journal of Forensic Sciences and Forensic Science International Genetics.

In The Last Decade

Roberto Puch‐Solis

22 papers receiving 388 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Roberto Puch‐Solis United Kingdom 10 305 147 95 91 69 24 416
Amanda B. Hepler United States 5 244 0.8× 69 0.5× 29 0.3× 22 0.2× 87 1.3× 10 419
Grayson R. Jackson United Kingdom 5 174 0.6× 45 0.3× 24 0.3× 47 0.5× 77 1.1× 10 376
Graham Jackson United Kingdom 10 140 0.5× 53 0.4× 20 0.2× 29 0.3× 70 1.0× 17 300
Nicole Egli Switzerland 9 155 0.5× 14 0.1× 126 1.3× 130 1.4× 47 0.7× 15 322
Simone Gittelson Switzerland 10 128 0.4× 85 0.6× 8 0.1× 14 0.2× 45 0.7× 18 231
Bernard Robertson New Zealand 8 124 0.4× 19 0.1× 30 0.3× 22 0.2× 124 1.8× 25 399
Timothy M. Palmbach United States 8 94 0.3× 86 0.6× 39 0.4× 12 0.1× 16 0.2× 13 319
Damien Abarno Australia 9 259 0.8× 215 1.5× 6 0.1× 23 0.3× 29 0.4× 19 351
Simon Baechler Switzerland 13 155 0.5× 89 0.6× 6 0.1× 46 0.5× 40 0.6× 29 461
Paul E. Kish United States 6 170 0.6× 50 0.3× 4 0.0× 113 1.2× 17 0.2× 9 372

Countries citing papers authored by Roberto Puch‐Solis

Since Specialization
Citations

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

Fields of papers citing papers by Roberto Puch‐Solis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Roberto Puch‐Solis. 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 Roberto Puch‐Solis. The network helps show where Roberto Puch‐Solis may publish in the future.

Co-authorship network of co-authors of Roberto Puch‐Solis

This figure shows the co-authorship network connecting the top 25 collaborators of Roberto Puch‐Solis. A scholar is included among the top collaborators of Roberto Puch‐Solis 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 Roberto Puch‐Solis. Roberto Puch‐Solis 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.
Mookiah, Muthu Rama Krishnan, et al.. (2025). Automated segmentation of the breech and firing pin faces of fired cartridge case images. Forensic Science International. 375. 112554–112554.
2.
Puch‐Solis, Roberto, Susan Pope, & Gillian Tully. (2024). Considerations on the application of a mutation model for Y-STR interpretation. Science & Justice. 64(2). 180–192. 2 indexed citations
3.
4.
Puch‐Solis, Roberto, et al.. (2023). A ground truth data set of gas chromatography mass spectrometry (GCMS) analysed synthesised methylenedioxymethylamphetamine (MDMA). Data in Brief. 47. 108931–108931. 1 indexed citations
5.
Mookiah, Muthu Rama Krishnan, Roberto Puch‐Solis, & Niamh Nic Daéid. (2023). Identification of bullets fired from air guns using machine and deep learning methods. Forensic Science International. 349. 111734–111734. 3 indexed citations
6.
7.
Puch‐Solis, Roberto, et al.. (2021). Interpretation of DNA data within the context of UK forensic science — investigation. Emerging Topics in Life Sciences. 5(3). 395–404. 7 indexed citations
8.
Puch‐Solis, Roberto, et al.. (2021). Interpretation of DNA data within the context of UK forensic science — evaluation. Emerging Topics in Life Sciences. 5(3). 405–413. 6 indexed citations
9.
Morrison, Geoffrey Stewart, et al.. (2021). Calculation of likelihood ratios for inference of biological sex from human skeletal remains. Forensic Science International Synergy. 3. 100202–100202. 7 indexed citations
10.
Pope, Susan, I.W. Evett, & Roberto Puch‐Solis. (2016). Adventitious match probability for autosomal profiles when primer binding site mutation is possible. Forensic Science International Genetics. 24. 143–147. 1 indexed citations
11.
Puch‐Solis, Roberto. (2014). A dropin peak height model. Forensic Science International Genetics. 11. 80–84. 18 indexed citations
12.
Puch‐Solis, Roberto & Tim Clayton. (2014). Evidential evaluation of DNA profiles using a discrete statistical model implemented in the DNA LiRa software. Forensic Science International Genetics. 11. 220–228. 21 indexed citations
13.
Puch‐Solis, Roberto, Lauren R. Rodgers, Susan Pope, et al.. (2013). Evaluating forensic DNA profiles using peak heights, allowing for multiple donors, allelic dropout and stutters. Forensic Science International Genetics. 7(5). 555–563. 64 indexed citations
14.
Hopwood, Andrew J., et al.. (2012). Consideration of the probative value of single donor 15-plex STR profiles in UK populations and its presentation in UK courts. Science & Justice. 52(3). 185–190. 9 indexed citations
15.
Puch‐Solis, Roberto, et al.. (2012). Assessing the probative value of DNA evidence: guidance for judges, lawyers, forensic scientists and expert witnesses. Nottingham ePrints (University of Nottingham). 5 indexed citations
16.
Puch‐Solis, Roberto, Amanda Kirkham, Phillipa Gill, et al.. (2010). Practical determination of the low template DNA threshold. Forensic Science International Genetics. 5(5). 422–427. 11 indexed citations
17.
Puch‐Solis, Roberto, Susan Pope, & I.W. Evett. (2010). Calculating likelihood ratios for a mixed DNA profile when a contribution from a genetic relative of a suspect is proposed. Science & Justice. 50(4). 205–209. 6 indexed citations
18.
Gill, Peter, Roberto Puch‐Solis, & James M. Curran. (2009). The low-template-DNA (stochastic) threshold—Its determination relative to risk analysis for national DNA databases. Forensic Science International Genetics. 3(2). 104–111. 62 indexed citations
19.
Neumann, Cédric, et al.. (2006). Computation of Likelihood Ratios in Fingerprint Identification for Configurations of Three Minutiæ. Journal of Forensic Sciences. 51(6). 1255–1266. 60 indexed citations
20.
Neumann, Cédric, et al.. (2006). Computation of Likelihood Ratios in Fingerprint Identification for Configurations of Any Number of Minutiæ. Journal of Forensic Sciences. 52(1). 54–64. 102 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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