Keith Noto

3.5k total citations · 1 hit paper
13 papers, 938 citations indexed

About

Keith Noto is a scholar working on Molecular Biology, Artificial Intelligence and Genetics. According to data from OpenAlex, Keith Noto has authored 13 papers receiving a total of 938 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 4 papers in Artificial Intelligence and 4 papers in Genetics. Recurrent topics in Keith Noto's work include Genetic Associations and Epidemiology (4 papers), RNA and protein synthesis mechanisms (3 papers) and Network Security and Intrusion Detection (2 papers). Keith Noto is often cited by papers focused on Genetic Associations and Epidemiology (4 papers), RNA and protein synthesis mechanisms (3 papers) and Network Security and Intrusion Detection (2 papers). Keith Noto collaborates with scholars based in United States. Keith Noto's co-authors include Charles Elkan, Donna K. Slonim, Carla E. Brodley, Jake Byrnes, Natalie M. Myres, Julie M. Granka, Amir R. Kermany, Catherine A. Ball, Kristin A. Rand and J. Graham Ruby and has published in prestigious journals such as Nature Communications, Bioinformatics and Genetics.

In The Last Decade

Keith Noto

13 papers receiving 901 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.

Learning classifiers from only positive and unlabeled data

2008 606 citations Charles Elkan, Keith Noto profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Keith Noto United States	8	475	189	106	86	82	13	938
Bo Xu China	18	473 1.0×	297 1.6×	21 0.2×	74 0.9×	29 0.4×	90	1.2k
Randal S. Olson United States	13	391 0.8×	141 0.7×	110 1.0×	79 0.9×	56 0.7×	29	1.1k
Lian Li China	21	308 0.6×	258 1.4×	58 0.5×	125 1.5×	377 4.6×	172	1.4k
Yang Xiang China	19	598 1.3×	313 1.7×	25 0.2×	72 0.8×	59 0.7×	61	1.2k
Veronica Vinciotti United Kingdom	18	236 0.5×	437 2.3×	105 1.0×	38 0.4×	28 0.3×	56	1.2k
Guzmán Santafé Spain	8	273 0.6×	378 2.0×	62 0.6×	49 0.6×	27 0.3×	16	914
Seung‐Ho Kang South Korea	15	106 0.2×	51 0.3×	75 0.7×	25 0.3×	108 1.3×	63	627
Matthew A. Reyna United States	14	355 0.7×	230 1.2×	51 0.5×	43 0.5×	8 0.1×	30	1.3k
Jianhua Z. Huang United States	18	378 0.8×	247 1.3×	81 0.8×	79 0.9×	12 0.1×	39	1.4k
Robert G. Staudte Australia	17	114 0.2×	102 0.5×	44 0.4×	66 0.8×	29 0.4×	54	1.4k

Countries citing papers authored by Keith Noto

Since Specialization

Citations

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

Fields of papers citing papers by Keith Noto

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Keith Noto

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

All Works

Sort: Min cites: Since: Top N: Style:

13 of 13 papers shown

1.

Noto, Keith & Luong Ruiz. (2022). Accurate genome-wide phasing from IBD data. BMC Bioinformatics. 23(1). 502–502. 3 indexed citations

2.

Wang, Yong, Shiya Song, Joshua G. Schraiber, et al.. (2021). Ancestry inference using reference labeled clusters of haplotypes. BMC Bioinformatics. 22(1). 459–459. 4 indexed citations

3.

Wright, Kevin M., Kristin A. Rand, Amir R. Kermany, et al.. (2019). A Prospective Analysis of Genetic Variants Associated with Human Lifespan. G3 Genes Genomes Genetics. 9(9). 2863–2878. 35 indexed citations

4.

Ruby, J. Graham, Kevin M. Wright, Kristin A. Rand, et al.. (2018). Estimates of the Heritability of Human Longevity Are Substantially Inflated due to Assortative Mating. Genetics. 210(3). 1109–1124. 123 indexed citations

5.

Han, Eunjung, Peter Carbonetto, Yong Wang, et al.. (2017). Clustering of 770,000 genomes reveals post-colonial population structure of North America. Nature Communications. 8(1). 14238–14238. 61 indexed citations

6.

Noto, Keith, et al.. (2015). CSAX: Characterizing Systematic Anomalies in eXpression Data. Journal of Computational Biology. 22(5). 402–413. 4 indexed citations

7.

Park, Jisoo, et al.. (2014). Finding Novel Molecular Connections between Developmental Processes and Disease. PLoS Computational Biology. 10(5). e1003578–e1003578. 9 indexed citations

8.

Noto, Keith, Carla E. Brodley, & Donna K. Slonim. (2011). FRaC: a feature-modeling approach for semi-supervised and unsupervised anomaly detection. Data Mining and Knowledge Discovery. 25(1). 109–133. 52 indexed citations

9.

Noto, Keith, et al.. (2010). Anomaly Detection Using an Ensemble of Feature Models. PubMed. 953–958. 23 indexed citations

10.

Noto, Keith & Mark Craven. (2008). Learning Hidden Markov Models for Regression using Path Aggregation.. PubMed. 2008. 444–451. 2 indexed citations

11.

Elkan, Charles & Keith Noto. (2008). Learning classifiers from only positive and unlabeled data. 213–220. 606 indexed citations breakdown →

12.

Noto, Keith & Mark Craven. (2007). Learning probabilistic models ofcis-regulatory modules that represent logical and spatial aspects. Bioinformatics. 23(2). e156–e162. 13 indexed citations

13.

Noto, Keith & Mark Craven. (2006). A specialized learner for inferring structured cis-regulatory modules. BMC Bioinformatics. 7(1). 528–528. 3 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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