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Cesare Furlanello

Cesare Furlanello

D-Index & Metrics

Computer Science

D-Index
40
Citations
11919
World Ranking
9069
National Ranking
255

Overview

Cesare Furlanello is affiliated with the Fondazione Bruno Kessler in Italy. Their research spans multiple areas intersecting biochemistry, genetics, molecular biology, and medicine, with significant contributions to both fundamental and applied scientific fields.

The main fields of study associated with their work include Biochemistry, Genetics and Molecular Biology and Medicine. Within these, Furlanello has focused particularly on subfields such as Molecular Biology, Cognitive Neuroscience, Genetics, Artificial Intelligence, and Radiology, Nuclear Medicine and Imaging.

Key topics explored in their research include Autism Spectrum Disorder Research, AI in cancer detection, EEG and Brain-Computer Interfaces, Cell Image Analysis Techniques, Non-Invasive Vital Sign Monitoring, Radiomics and Machine Learning in Medical Imaging, and Cancer Genomics and Diagnostics.

Among recent notable publications are:

  • Transparency and reproducibility in artificial intelligence, 2020, Nature
  • Reporting guidelines for human microbiome research: the STORMS checklist, 2021, Nature Medicine
  • Cellular and gene signatures of tumor-infiltrating dendritic cells and natural-killer cells predict prognosis of neuroblastoma, 2020, Nature Communications
  • Precipitation Nowcasting with Orographic Enhanced Stacked Generalization: Improving Deep Learning Predictions on Extreme Events, 2020, Atmosphere
  • A verified genomic reference sample for assessing performance of cancer panels detecting small variants of low allele frequency, 2021, Genome Biology

Furlanello has published frequently in venues including Sensors, bioRxiv (Cold Spring Harbor Laboratory), Zenodo (CERN European Organization for Nuclear Research), Emerging Trends in Drugs Addictions and Health, and Nature Communications.

Frequent collaborators in their research include Giuseppe Jurman, Paola Venuti, Luca Coviello, Marco Chierici, and Nicole Bussola.

Best Publications

  • The Microarray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

    Leming Shi;Gregory Campbell;Wendell D. Jones;Fabien Campagne

  • A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium

    Zhenqiang Su;Paweł P. Łabaj;Sheng Li;Jean Thierry-Mieg

  • Recursive feature elimination with random forest for PTR-MS analysis of agroindustrial products

    Pablo M. Granitto;Cesare Furlanello;Franco Biasioli;Flavia Gasperi

  • Repeatability of published microarray gene expression analyses.

    John P A Ioannidis;David B Allison;Catherine A Ball;Issa Coulibaly

  • The concordance between RNA-seq and microarray data depends on chemical treatment and transcript abundance

    Charles Wang;Binsheng Gong;Pierre R. Bushel;Jean Thierry-Mieg

  • Comparison of RNA-seq and microarray-based models for clinical endpoint prediction.

    Wenqian Zhang;Ying Yu;Falk Hertwig;Falk Hertwig;Jean Thierry-Mieg

  • A Comparison of MCC and CEN Error Measures in Multi-Class Prediction

    Giuseppe Jurman;Samantha Riccadonna;Cesare Furlanello

  • minerva and minepy

    Davide Albanese;Michele Filosi;Roberto Visintainer;Samantha Riccadonna

  • Predicting habitat suitability with machine learning models: The potential area of Pinus sylvestris L. in the Iberian Peninsula

    Marta Benito Garzón;Radim Blazek;Markus Neteler;Rut Sánchez de Dios

  • Deep representation learning of electronic health records to unlock patient stratification at scale.

    Isotta Landi;Benjamin S. Glicksberg;Hao-Chih Lee;Sarah T. Cherng

  • Entropy-based gene ranking without selection bias for the predictive classification of microarray data

    Cesare Furlanello;Maria Serafini;Stefano Merler;Giuseppe Jurman

  • Algebraic stability indicators for ranked lists in molecular profiling

    Giuseppe Jurman;Stefano Merler;Annalisa Barla;Silvano Paoli

  • Phylogenetic convolutional neural networks in metagenomics

    Diego Fioravanti;Diego Fioravanti;Ylenia Giarratano;Valerio Maggio;Claudio Agostinelli

  • An accelerated procedure for recursive feature ranking on microarray data

    C. Furlanello;M. Serafini;S. Merler;G. Jurman

  • Geographical information systems and bootstrap aggregation (bagging) of tree-based classifiers for Lyme disease risk prediction in Trentino, Italian Alps.

    Annapaola Rizzoli;Stefano Merler;Cesare furlanello;Claudio Genchi

  • Deep learning for automatic stereotypical motor movement detection using wearable sensors in autism spectrum disorders

    Nastaran Mohammadian Rad;Nastaran Mohammadian Rad;Nastaran Mohammadian Rad;Seyed Mostafa Kia;Calogero Zarbo;Twan van Laarhoven

  • Machine learning methods for predictive proteomics

    Annalisa Barla;Giuseppe Jurman;Samantha Riccadonna;Stefano Merler

  • Precipitation Nowcasting with Orographic Enhanced Stacked Generalization: Improving Deep Learning Predictions on Extreme Events

    Gabriele Franch;Daniele Nerini;Marta Pendesini;Luca Coviello

  • Modern data mining tools in descriptive sensory analysis: A case study with a Random forest approach

    P.M. Granitto;F. Gasperi;F. Biasioli;E. Trainotti

  • mlpy: Machine Learning Python

    Davide Albanese;Roberto Visintainer;Stefano Merler;Samantha Riccadonna

  • Rapid and non-destructive identification of strawberry cultivars by direct PTR-MS headspace analysis and data mining techniques

    Pablo M. Granitto;Franco Biasioli;Eugenio Aprea;Daniela Mott

  • cmine, minerva & minepy: a C engine for the MINE suite and its R and Python wrappers

    Davide Albanese;Michele Filosi;Roberto Visintainer;Samantha Riccadonna

Frequent Co-Authors

Giuseppe Jurman
Giuseppe Jurman Fondazione Bruno Kessler
Huixiao Hong
Huixiao Hong United States Food and Drug Administration
Weida Tong
Weida Tong National Center for Toxicological Research
Leming Shi
Leming Shi Fudan University
Gianluca Esposito
Gianluca Esposito University of Trento
Paola Venuti
Paola Venuti University of Trento
Wenzhong Xiao
Wenzhong Xiao Harvard University
Matthias Fischer
Matthias Fischer University of Cologne
Yuri Nikolsky
Yuri Nikolsky F1 Genomics
Pierre R. Bushel
Pierre R. Bushel National Institutes of Health

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