Berkley Shands

1.1k total citations · 2 hit papers
9 papers, 843 citations indexed

About

Berkley Shands is a scholar working on Molecular Biology, Computer Networks and Communications and Hardware and Architecture. According to data from OpenAlex, Berkley Shands has authored 9 papers receiving a total of 843 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 3 papers in Computer Networks and Communications and 3 papers in Hardware and Architecture. Recurrent topics in Berkley Shands's work include Parallel Computing and Optimization Techniques (3 papers), Advanced Data Storage Technologies (3 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). Berkley Shands is often cited by papers focused on Parallel Computing and Optimization Techniques (3 papers), Advanced Data Storage Technologies (3 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). Berkley Shands collaborates with scholars based in United States and Switzerland. Berkley Shands's co-authors include Elena Deych, William D. Shannon, Erica Sodergren, George M. Weinstock, Yanjiao Zhou, Carla Hall-Moore, Julie Hoffmann, Laura Linneman, Aaron Hamvas and Phillip I. Tarr and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Lancet and PLoS ONE.

In The Last Decade

Berkley Shands

9 papers receiving 827 citations

Hit Papers

Patterned progression of ... 2014 2026 2018 2022 2014 2016 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Berkley Shands United States 6 521 395 167 138 113 9 843
Julie Hoffmann United States 6 542 1.0× 401 1.0× 194 1.2× 155 1.1× 130 1.2× 8 847
Laura Linneman United States 9 585 1.1× 410 1.0× 230 1.4× 157 1.1× 152 1.3× 14 917
Tom Skeath United Kingdom 9 411 0.8× 281 0.7× 144 0.9× 126 0.9× 75 0.7× 12 629
Maka Mshvildadze United States 6 296 0.6× 266 0.7× 89 0.5× 66 0.5× 61 0.5× 7 490
Claude Billeaud France 15 619 1.2× 107 0.3× 200 1.2× 115 0.8× 81 0.7× 52 896
Anders Brunse Denmark 16 294 0.6× 274 0.7× 122 0.7× 79 0.6× 78 0.7× 36 730
Joann Romano-Keeler United States 12 133 0.3× 187 0.5× 92 0.6× 79 0.6× 68 0.6× 16 594
Thao Ho United States 13 235 0.5× 179 0.5× 112 0.7× 154 1.1× 48 0.4× 30 510
Dorota Gieruszczak‐Białek Poland 13 165 0.3× 219 0.6× 33 0.2× 41 0.3× 71 0.6× 19 655
Jean Bresson France 12 107 0.2× 102 0.3× 50 0.3× 55 0.4× 53 0.5× 37 620

Countries citing papers authored by Berkley Shands

Since Specialization
Citations

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

Fields of papers citing papers by Berkley Shands

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Berkley Shands. 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 Berkley Shands. The network helps show where Berkley Shands may publish in the future.

Co-authorship network of co-authors of Berkley Shands

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

All Works

9 of 9 papers shown
1.
Johnson, Jethro S., Xin Zhou, Elena Deych, et al.. (2019). New statistical method identifies cytokines that distinguish stool microbiomes. Scientific Reports. 9(1). 20082–20082. 4 indexed citations
2.
Deych, Elena, Berkley Shands, Meghan C. Campbell, et al.. (2019). Detecting associations between intact connectomes and clinical covariates using recursive partitioning object‐oriented data analysis. Statistics in Medicine. 38(29). 5486–5496. 1 indexed citations
3.
Warner, Barbara, Elena Deych, Yanjiao Zhou, et al.. (2016). Gut bacteria dysbiosis and necrotising enterocolitis in very low birthweight infants: a prospective case-control study. The Lancet. 387(10031). 1928–1936. 347 indexed citations breakdown →
4.
Rosa, Patricio S. La, Elena Deych, Berkley Shands, et al.. (2015). Gibbs distribution for statistical analysis of graphical data with a sample application to fcMRI brain images. Statistics in Medicine. 35(4). 566–580. 18 indexed citations
5.
Rosa, Patricio S. La, Barbara Warner, Yanjiao Zhou, et al.. (2014). Patterned progression of bacterial populations in the premature infant gut. Proceedings of the National Academy of Sciences. 111(34). 12522–12527. 414 indexed citations breakdown →
6.
Rosa, Patricio S. La, Berkley Shands, Elena Deych, et al.. (2012). Statistical Object Data Analysis of Taxonomic Trees from Human Microbiome Data. PLoS ONE. 7(11). e48996–e48996. 14 indexed citations
7.
Shands, Berkley, et al.. (2008). Financial Monte Carlo simulation on architecturally diverse systems. Open Scholarship Institutional Repository (Washington University in St. Louis). 1–7. 23 indexed citations
8.
Chamberlain, Roger D. & Berkley Shands. (2007). Direct-Attached Disk Subsystem Performance Assessment. 71–78. 2 indexed citations
9.
Franklin, M., et al.. (2004). An architecture for fast processing of large unstructured data sets. 280–287. 20 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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