Gregory L. Finney

5.5k total citations · 1 hit paper
7 papers, 3.9k citations indexed

About

Gregory L. Finney is a scholar working on Molecular Biology, Spectroscopy and Genetics. According to data from OpenAlex, Gregory L. Finney has authored 7 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 5 papers in Spectroscopy and 1 paper in Genetics. Recurrent topics in Gregory L. Finney's work include Advanced Proteomics Techniques and Applications (5 papers), Mass Spectrometry Techniques and Applications (5 papers) and Metabolomics and Mass Spectrometry Studies (3 papers). Gregory L. Finney is often cited by papers focused on Advanced Proteomics Techniques and Applications (5 papers), Mass Spectrometry Techniques and Applications (5 papers) and Metabolomics and Mass Spectrometry Studies (3 papers). Gregory L. Finney collaborates with scholars based in United States. Gregory L. Finney's co-authors include Michael J. MacCoss, Barbara Frewen, Daniela M. Tomazela, Nicholas Shulman, D.C. Liebler, David L. Tabb, Brendan MacLean, Matthew Chambers, Michael R. Hoopmann and Catherine M. Eakin and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Bioinformatics and Analytical Chemistry.

In The Last Decade

Gregory L. Finney

7 papers receiving 3.9k citations

Hit 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.

Skyline: an open source document editor for creating and analyzing targeted proteomics experiments

2010 3.5k citations Brendan MacLean, Daniela M. Tomazela et al. Bioinformatics profile →

Peers

Gregory L. Finney

MB

SPECT

ONCOL

GENET

IMMUN

Jeffrey C. Silva United States

Christie L. Hunter United States

Pedro Navarro Spain

Gerhard Mayer Germany

Nathalie Selevsek Switzerland

Johannes P.C. Vissers United Kingdom

Hannes Hahne Germany

Nicholas Shulman United States

Mary F. Lopez United States

Jeffrey C. Silva United States

Gregory L. Finney

3.2k ×1.2

MB

1.4k ×1.0

SPECT

403 ×1.4

ONCOL

287 ×1.0

GENET

276 ×1.1

IMMUN

Citations per year, relative to Gregory L. Finney Gregory L. Finney (= 1×) peers Jeffrey C. Silva

Countries citing papers authored by Gregory L. Finney

Since Specialization

Citations

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

Fields of papers citing papers by Gregory L. Finney

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gregory L. Finney. 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 Gregory L. Finney. The network helps show where Gregory L. Finney may publish in the future.

Co-authorship network of co-authors of Gregory L. Finney

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

All Works

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7 of 7 papers shown

1.

MacLean, Brendan, Daniela M. Tomazela, Nicholas Shulman, et al.. (2010). Skyline: an open source document editor for creating and analyzing targeted proteomics experiments. Bioinformatics. 26(7). 966–968. 3488 indexed citations breakdown →

2.

Cooper, Sara J., Gregory L. Finney, Sven Nelson, et al.. (2010). High-throughput profiling of amino acids in strains of the Saccharomyces cerevisiae deletion collection. Genome Research. 20(9). 1288–1296. 24 indexed citations

3.

Kline, Kelli G., Gregory L. Finney, & C. C. Wu. (2009). Quantitative strategies to fuel the merger of discovery and hypothesis-driven shotgun proteomics. Briefings in Functional Genomics and Proteomics. 8(2). 114–125. 13 indexed citations

4.

Bern, Marshall, Gregory L. Finney, Michael R. Hoopmann, et al.. (2009). Deconvolution of Mixture Spectra from Ion-Trap Data-Independent-Acquisition Tandem Mass Spectrometry. Analytical Chemistry. 82(3). 833–841. 93 indexed citations

5.

Finney, Gregory L., Adele Blackler, Michael R. Hoopmann, et al.. (2008). Label-Free Comparative Analysis of Proteomics Mixtures Using Chromatographic Alignment of High-Resolution μLC−MS Data. Analytical Chemistry. 80(4). 961–971. 52 indexed citations

6.

Eakin, Catherine M., Michael J. MacCoss, Gregory L. Finney, & Rachel E. Klevit. (2007). Estrogen receptor α is a putative substrate for the BRCA1 ubiquitin ligase. Proceedings of the National Academy of Sciences. 104(14). 5794–5799. 138 indexed citations

7.

Hoopmann, Michael R., Gregory L. Finney, & Michael J. MacCoss. (2007). High-Speed Data Reduction, Feature Detection, and MS/MS Spectrum Quality Assessment of Shotgun Proteomics Data Sets Using High-Resolution Mass Spectrometry. Analytical Chemistry. 79(15). 5620–5632. 141 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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