World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
51
Citations
18664
World Ranking
5210
National Ranking
2391

Research.com Recognitions

  • 2018 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 2016 - ACM Distinguished Member
  • 2016 - IEEE Fellow For contributions to computational biology and data mining
  • 2014 - ACM Senior Member

Overview

Stefano Lonardi is affiliated with the University of California, Riverside in the United States. Their research spans fields including Biochemistry, Genetics and Molecular Biology, as well as Agricultural and Biological Sciences. The scientist's work particularly focuses on subfields such as Molecular Biology, Plant Science, Parasitology, Public Health, Environmental and Occupational Health, and Genetics.

Their research topics cover a range of areas including RNA and protein synthesis mechanisms, agricultural pest management studies, genomics and phylogenetic studies, CRISPR and genetic engineering, chromosomal and genetic variations, vector-borne infectious diseases, and RNA modifications and cancer.

Stefano Lonardi's recent publications demonstrate engagement with diverse biological and computational challenges. Notable recent papers include:

  • "Mustache: multi-scale detection of chromatin loops from Hi-C and Micro-C maps using scale-space representation," 2020, Genome Biology
  • "Genome-wide functional screens enable the prediction of high activity CRISPR-Cas9 and -Cas12a guides in Yarrowia lipolytica," 2022, Nature Communications
  • "A view of the pan-genome of domesticated Cowpea ( Vigna unguiculata [L.] Walp.)," 2023, The Plant Genome
  • "Karyotype variation, spontaneous genome rearrangements affecting chemical insensitivity, and expression level polymorphisms in the plant pathogen Phytophthora infestans revealed using its first chromosome-scale assembly," 2022, PLoS Pathogens
  • "Babesia duncani multi-omics identifies virulence factors and drug targets," 2023, Nature Microbiology

Frequent collaborators in their work include Karine G. Le Roch, Sakshar Chakravarty, Ian Wheeldon, Qihua Liang, and Timothy J. Close. Publication venues with multiple contributions include bioRxiv (Cold Spring Harbor Laboratory), Genome Biology, Genome Research, BMC Bioinformatics, and NAR Genomics and Bioinformatics.

Stefano Lonardi has received professional recognition such as being named a Fellow of the American Association for the Advancement of Science (AAAS) in 2018. They have also been honored as an ACM Distinguished Member in 2016, an IEEE Fellow the same year for contributions to computational biology and data mining, and an ACM Senior Member in 2014.

Best Publications

  • A symbolic representation of time series, with implications for streaming algorithms

    Jessica Lin;Eamonn Keogh;Stefano Lonardi;Bill Chiu

  • A Whole-Genome Assembly of Drosophila

    Eugene W. Myers;Granger G. Sutton;Art L. Delcher;Ian M. Dew

  • Experiencing SAX: a novel symbolic representation of time series

    Jessica Lin;Eamonn Keogh;Li Wei;Stefano Lonardi

  • A physical, genetic and functional sequence assembly of the barley genome

    Klaus F.X. Mayer;Robbie Waugh;Peter Langridge;Timothy J. Close

  • Towards parameter-free data mining

    Eamonn Keogh;Stefano Lonardi;Chotirat Ann Ratanamahatana

  • Probabilistic discovery of time series motifs

    Bill Chiu;Eamonn Keogh;Stefano Lonardi

  • CLARK: fast and accurate classification of metagenomic and genomic sequences using discriminative k-mers

    Rachid Ounit;Steve Wanamaker;Timothy J Close;Stefano Lonardi

  • Efficient and accurate construction of genetic linkage maps from the minimum spanning tree of a graph.

    Yonghui Wu;Prasanna R. Bhat;Timothy J. Close;Stefano Lonardi

  • Finding surprising patterns in a time series database in linear time and space

    Eamonn Keogh;Stefano Lonardi;Bill 'Yuan-chi' Chiu

  • Composition Profiler: a tool for discovery and visualization of amino acid composition differences

    Vladimir Vacic;Vladimir N Uversky;Vladimir N Uversky;A Keith Dunker;Stefano Lonardi

  • Comprehensive benchmarking and ensemble approaches for metagenomic classifiers.

    Alexa B. R. McIntyre;Rachid Ounit;Ebrahim Afshinnekoo;Ebrahim Afshinnekoo;Robert J. Prill

  • Mining motifs in massive time series databases

    P. Patel;E. Keogh;J. Lin;S. Lonardi

  • Mustache: multi-scale detection of chromatin loops from Hi-C and Micro-C maps using scale-space representation.

    Abbas Roayaei Ardakany;Abbas Roayaei Ardakany;Halil Tuvan Gezer;Halil Tuvan Gezer;Stefano Lonardi;Ferhat Ay;Ferhat Ay

  • Visually mining and monitoring massive time series

    Jessica Lin;Eamonn Keogh;Stefano Lonardi;Jeffrey P. Lankford

  • Time-series Bitmaps: a Practical Visualization Tool for Working with Large Time Series Databases.

    Nitin Kumar;Venkata Nishanth Lolla;Eamonn J. Keogh;Stefano Lonardi

  • Assignment of Orthologous Genes via Genome Rearrangement

    Xin Chen;Jie Zheng;Zheng Fu;Peng Nan

  • Assumption-free anomaly detection in time series

    Li Wei;Nitin Kumar;Venkata Lolla;Eamonn J. Keogh

  • Visualizing and discovering non-trivial patterns in large time series databases

    Jessica Lin;Eamonn Keogh;Stefano Lonardi

  • A novel bit level time series representation with implication of similarity search and clustering

    Chotirat Ratanamahatana;Eamonn Keogh;Anthony J. Bagnall;Stefano Lonardi

  • Compression-based data mining of sequential data

    Eamonn Keogh;Stefano Lonardi;Chotirat Ann Ratanamahatana;Li Wei

  • This Provisional PDF corresponds to the article as it appeared upon acceptance. Fully formatted PDF and full text (HTML) versions will be made available soon. Development and implementation of high-throughput SNP genotyping in barley

    Stefano Lonardi;Luke Ramsay;Steve Wanamaker;Mikeal L Roose

Frequent Co-Authors

Timothy J. Close
Timothy J. Close University of California, Riverside
Eamonn Keogh
Eamonn Keogh University of California, Riverside
Yonghui Wu
Yonghui Wu Google (United States)
Ming-Cheng Luo
Ming-Cheng Luo University of California, Davis
Gary J. Muehlbauer
Gary J. Muehlbauer University of Minnesota
Tao Jiang
Tao Jiang University of California, Riverside
Karine G. Le Roch
Karine G. Le Roch University of California, Riverside
Nils Stein
Nils Stein University of Western Australia
Philip A. Roberts
Philip A. Roberts University of California, Riverside
Frank M. You
Frank M. You Agriculture and Agriculture-Food Canada

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