Michael F. Lin

14.6k total citations · 3 hit papers
13 papers, 6.3k citations indexed

About

Michael F. Lin is a scholar working on Molecular Biology, Genetics and Plant Science. According to data from OpenAlex, Michael F. Lin has authored 13 papers receiving a total of 6.3k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 4 papers in Genetics and 3 papers in Plant Science. Recurrent topics in Michael F. Lin's work include RNA and protein synthesis mechanisms (7 papers), Genomics and Phylogenetic Studies (7 papers) and Genetic diversity and population structure (3 papers). Michael F. Lin is often cited by papers focused on RNA and protein synthesis mechanisms (7 papers), Genomics and Phylogenetic Studies (7 papers) and Genetic diversity and population structure (3 papers). Michael F. Lin collaborates with scholars based in United States, Switzerland and Denmark. Michael F. Lin's co-authors include Manolis Kellis, Irwin Jungreis, Eric S. Lander, L B Chen, Thomas W. Smith, S T Smiley, Aileen B. Chen, G Steele, Martin Reers and Ido Amit and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Bioinformatics.

In The Last Decade

Michael F. Lin

13 papers receiving 6.2k 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.

Chromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammals

2009 3.3k citations Mitchell Guttman, Ido Amit et al. Nature profile →
Intracellular heterogeneity in mitochondrial membrane potentials revealed by a J-aggregate-forming lipophilic cation JC-1.

1991 1.4k citations S T Smiley, Martin Reers et al. Proceedings of the National Academy of Sciences profile →
PhyloCSF: a comparative genomics method to distinguish protein coding and non-coding regions

2011 727 citations Michael F. Lin, Irwin Jungreis et al. Bioinformatics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michael F. Lin United States	12	5.0k	3.5k	446	312	295	13	6.3k
Thomas Preiß Australia	47	9.0k 1.8×	2.8k 0.8×	400 0.9×	514 1.6×	269 0.9×	110	10.0k
J. Pablo Radicella France	38	4.3k 0.9×	1.1k 0.3×	632 1.4×	564 1.8×	235 0.8×	98	5.3k
Xin Liu China	39	4.5k 0.9×	957 0.3×	427 1.0×	388 1.2×	335 1.1×	210	6.0k
Sonja Hess United States	43	4.9k 1.0×	928 0.3×	592 1.3×	205 0.7×	1.1k 3.7×	141	6.9k
Michael J. Sweredoski United States	42	5.1k 1.0×	689 0.2×	586 1.3×	257 0.8×	999 3.4×	89	6.4k
Rajendra Prasad United States	52	8.3k 1.6×	1.8k 0.5×	987 2.2×	548 1.8×	305 1.0×	141	9.6k
Anthony K. L. Leung United States	40	5.6k 1.1×	1.4k 0.4×	280 0.6×	362 1.2×	305 1.0×	81	7.3k
Shu‐Bing Qian United States	38	7.2k 1.4×	2.3k 0.7×	379 0.8×	202 0.6×	866 2.9×	68	9.0k
Jianping Jin United States	30	4.3k 0.8×	783 0.2×	511 1.1×	181 0.6×	586 2.0×	51	5.4k
Denis L. J. Lafontaine Belgium	48	7.1k 1.4×	1.3k 0.4×	250 0.6×	354 1.1×	160 0.5×	101	7.7k

Countries citing papers authored by Michael F. Lin

Since Specialization

Citations

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

Fields of papers citing papers by Michael F. Lin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael F. Lin. 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 Michael F. Lin. The network helps show where Michael F. Lin may publish in the future.

Co-authorship network of co-authors of Michael F. Lin

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

All Works

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13 of 13 papers shown

Lin, Michael F., et al.. (2019). Study on diagnostic value of P1NP and β-CTX in bone metastasis of patients with breast cancer and the correlation between them.. PubMed. 23(12). 5277–5284. 7 indexed citations

Jungreis, Irwin, et al.. (2016). Evolutionary Dynamics of Abundant Stop Codon Readthrough. Molecular Biology and Evolution. 33(12). 3108–3132. 38 indexed citations

Sealfon, Rachel, Michael F. Lin, Irwin Jungreis, et al.. (2015). FRESCo: finding regions of excess synonymous constraint in diverse viruses. Genome Biology. 16(1). 38–38. 26 indexed citations

Jungreis, Irwin, Michael F. Lin, Rebecca Spokony, et al.. (2011). Evidence of abundant stop codon readthrough in Drosophila and other metazoa. Genome Research. 21(12). 2096–2113. 155 indexed citations

Hubisz, Melissa J., Michael F. Lin, Manolis Kellis, & Adam Siepel. (2011). Error and Error Mitigation in Low-Coverage Genome Assemblies. PLoS ONE. 6(2). e17034–e17034. 29 indexed citations

Lin, Michael F., Pouya Kheradpour, Stefan Washietl, et al.. (2011). Locating protein-coding sequences under selection for additional, overlapping functions in 29 mammalian genomes. Genome Research. 21(11). 1916–1928. 72 indexed citations

Lin, Michael F., Irwin Jungreis, & Manolis Kellis. (2011). PhyloCSF: a comparative genomics method to distinguish protein coding and non-coding regions. Bioinformatics. 27(13). i275–i282. 727 indexed citations breakdown →

Guttman, Mitchell, Ido Amit, Manuel Garber, et al.. (2009). Chromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammals. Nature. 458(7235). 223–227. 3283 indexed citations breakdown →

Lin, Michael F. & Vamsidhar R. Narra. (2008). Developing role of magnetic resonance imaging in Crohn??s disease. Current Opinion in Gastroenterology. 24(2). 135–140. 24 indexed citations

10.

Lin, Michael F., et al.. (2008). Performance and Scalability of Discriminative Metrics for Comparative Gene Identification in 12 Drosophila Genomes. PLoS Computational Biology. 4(4). e1000067–e1000067. 37 indexed citations

11.

Lin, Michael F., Joseph W. Carlson, Madeline A. Crosby, et al.. (2007). Revisiting the protein-coding gene catalog ofDrosophila melanogasterusing 12 fly genomes. Genome Research. 17(12). 1823–1836. 115 indexed citations

12.

Clamp, Michèle, Ben Fry, Xiaohui Xie, et al.. (2007). Distinguishing protein-coding and noncoding genes in the human genome. Proceedings of the National Academy of Sciences. 104(49). 19428–19433. 404 indexed citations

13.

Smiley, S T, Martin Reers, Michael F. Lin, et al.. (1991). Intracellular heterogeneity in mitochondrial membrane potentials revealed by a J-aggregate-forming lipophilic cation JC-1.. Proceedings of the National Academy of Sciences. 88(9). 3671–3675. 1379 indexed citations breakdown →

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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