Joseph M. Paggi

17.3k total citations · 3 hit papers
17 papers, 9.1k citations indexed

About

Joseph M. Paggi is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Organic Chemistry. According to data from OpenAlex, Joseph M. Paggi has authored 17 papers receiving a total of 9.1k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 7 papers in Cellular and Molecular Neuroscience and 3 papers in Organic Chemistry. Recurrent topics in Joseph M. Paggi's work include Neuropeptides and Animal Physiology (5 papers), RNA and protein synthesis mechanisms (5 papers) and RNA modifications and cancer (4 papers). Joseph M. Paggi is often cited by papers focused on Neuropeptides and Animal Physiology (5 papers), RNA and protein synthesis mechanisms (5 papers) and RNA modifications and cancer (4 papers). Joseph M. Paggi collaborates with scholars based in United States, Japan and United Kingdom. Joseph M. Paggi's co-authors include Steven L. Salzberg, Christopher Bennett, Daehwan Kim, Chanhee Park, Ron O. Dror, Brian K. Kobilka, Naomi R. Latorraca, Qianhui Qu, Georgios Skiniotis and Daniel Hilger and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Joseph M. Paggi

16 papers receiving 9.0k citations

Hit Papers

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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.

Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype

2019 7.9k citations Daehwan Kim, Joseph M. Paggi et al. Nature Biotechnology profile →
Structure of the µ-opioid receptor–Gi protein complex

2018 495 citations Antoine Koehl, Hongli Hu et al. Nature profile →
The Art and Science of Molecular Docking

2024 143 citations Joseph M. Paggi, Ron O. Dror et al. Annual Review of Biochemistry profile →

Peers

Countries citing papers authored by Joseph M. Paggi

Since Specialization

Citations

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

Fields of papers citing papers by Joseph M. Paggi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joseph M. Paggi. 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 Joseph M. Paggi. The network helps show where Joseph M. Paggi may publish in the future.

Co-authorship network of co-authors of Joseph M. Paggi

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

All Works

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17 of 17 papers shown

#	Work	Indexed citations
1	Toward decoding the mechanisms that shape sub-megabase-scale genome organization 2025 ·Current Opinion in Structural Biology ·Joseph M. Paggi, Bin Zhang	0
2	A non-canonical mechanism of GPCR activation 2024 ·Nature Communications ·Alexander S. Powers, (unknown), Joseph M. Paggi, Naomi R. Latorraca, (unknown), (unknown), Jun Lu, S.M. Soisson, Jennifer M. Johnston, Adam B. Weinglass, Ron O. Dror	10
3	The Art and Science of Molecular Docking breakdown → 2024 ·Annual Review of Biochemistry ·Joseph M. Paggi, (unknown), Ron O. Dror	143
4	Geometric Deep Learning for Structure-Based Ligand Design 2023 ·ACS Central Science ·Alexander S. Powers, Helen H. Yu, Patricia Suriana, (unknown), (unknown), Joseph M. Paggi, Ron O. Dror	25
5	Molecular mechanism of biased signaling at the kappa opioid receptor 2023 ·Nature Communications ·Amal El Daibani, Joseph M. Paggi, Kuglae Kim, (unknown), Petr Popov, Sarah M. Bernhard, B. Krumm, Reid H. J. Olsen, Jeffrey F. DiBerto, F. Ivy Carroll, Vsevolod Katritch, Bernhard Wünsch, Ron O. Dror, Tao Che	56
6	Insights into distinct signaling profiles of the µOR activated by diverse agonists 2022 ·Nature Chemical Biology ·Qianhui Qu, Weijiao Huang, Deniz Aydın, Joseph M. Paggi, Alpay B. Seven, Haoqing Wang, Soumen Chakraborty, Tao Che, Jeffrey F. DiBerto, Michael J. Robertson, Asuka Inoue, Carl‐Mikael Suomivuori, Bryan L. Roth, Susruta Majumdar, Ron O. Dror, Brian K. Kobilka, Georgios Skiniotis	72
7	Leveraging nonstructural data to predict structures and affinities of protein–ligand complexes 2021 ·Proceedings of the National Academy of Sciences ·Joseph M. Paggi, Julia A. Belk, Scott A. Hollingsworth, Nicolas Villanueva, Alexander S. Powers, Mary J. Clark, Augustine Chemparathy, (unknown), (unknown), Roger K. Sunahara, Ron O. Dror	21
8	Structural and functional characterization of G protein–coupled receptors with deep mutational scanning 2020 ·eLife ·Eric M. Jones, Nathan B. Lubock, AJ Venkatakrishnan, (unknown), Alex M. Tseng, Joseph M. Paggi, Naomi R. Latorraca, Daniel Cancilla, (unknown), Jessica E. Davis, M. Madan Babu, Ron O. Dror, Sriram Kosuri	84
9	Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype breakdown → 2019 ·Nature Biotechnology ·Daehwan Kim, Joseph M. Paggi, Chanhee Park, Christopher Bennett, Steven L. Salzberg	7900
10	S-CAP extends pathogenicity prediction to genetic variants that affect RNA splicing 2019 ·Nature Genetics ·Karthik A. Jagadeesh, Joseph M. Paggi, (unknown), Peter D. Stenson, D.N. Cooper, Jonathan A. Bernstein, Gill Bejerano	36
11	Structural mechanisms of selectivity and gating in anion channelrhodopsins 2018 ·Nature ·Hideaki Kato, Yoon Seok Kim, Joseph M. Paggi, Kathryn E. Evans, William E. Allen, Claire E. Richardson, Keiichi Inoue, Shota Ito, Charu Ramakrishnan, Lief E. Fenno, Keitaro Yamashita, Daniel Hilger, Soo Yeun Lee, A. Berndt, Kang Shen, Hideki Kandori, Ron O. Dror, Brian K. Kobilka, Karl Deisseroth	60
12	A sequence-based, deep learning model accurately predicts RNA splicing branchpoints 2018 ·RNA ·Joseph M. Paggi, Gill Bejerano	42
13	Numerous recursive sites contribute to accuracy of splicing in long introns in flies 2018 ·PLoS Genetics ·Athma A. Pai, Joseph M. Paggi, Paul Yan, Karen Adelman, Christopher B. Burge	12
14	Structure of the µ-opioid receptor–Gi protein complex breakdown → 2018 ·Nature ·Antoine Koehl, Hongli Hu, Shoji Maeda, Yan Zhang, Qianhui Qu, Joseph M. Paggi, Naomi R. Latorraca, Daniel Hilger, Roger Dawson, Hugues Matile, Gebhard F. X. Schertler, Sébastien Granier, William I. Weis, Ron O. Dror, Aashish Manglik, Georgios Skiniotis, Brian K. Kobilka	495
15	Crystal structure of the natural anion-conducting channelrhodopsin GtACR1 2018 ·Nature ·Yoon Seok Kim, Hideaki Kato, Keitaro Yamashita, Shota Ito, Keiichi Inoue, Charu Ramakrishnan, Lief E. Fenno, Kathryn E. Evans, Joseph M. Paggi, Ron O. Dror, Hideki Kandori, Brian K. Kobilka, Karl Deisseroth	76
16	Identification of new branch points and unconventional introns in Saccharomyces cerevisiae 2016 ·RNA ·(unknown), Joseph M. Paggi, Yuchun Guo, (unknown), Boris Zinshteyn, Eric T. Wang, Wendy V. Gilbert, David K. Gifford, Christopher B. Burge	27
17	Behaviour of rifaximin in foam formulation after intrauterine administration. 1990 ·(unknown), Joseph M. Paggi, (unknown), Maurizio Masi	2

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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