Search research articles
Contact Us
Filters
Showing results (1-10 of 9) with videos related to
Page
of 1
Sort By:
BMC Bioinformatics
|
June 9, 2015
Automatising the analysis of stochastic biochemical time-series
Giulio Caravagna, Luca De Sano, Marco Antoniotti
BMC Bioinformatics
|
April 27, 2019
Learning mutational graphs of individual tumour evolution from single-cell and multi-region sequencing data
Daniele Ramazzotti, Alex Graudenzi, Luca De Sano, et al.
Proteomics
|
December 22, 2017
SIMLR: A Tool for Large-Scale Genomic Analyses by Multi-Kernel Learning
Bo Wang, Daniele Ramazzotti, Luca De Sano, et al.
Bioinformatics (Oxford, England)
|
February 11, 2016
TRONCO: an R package for the inference of cancer progression models from heterogeneous genomic data
Luca De Sano, Giulio Caravagna, Daniele Ramazzotti, et al.
Proceedings of the National Academy of Sciences of the United States of America
|
July 1, 2016
Algorithmic methods to infer the evolutionary trajectories in cancer progression
Giulio Caravagna, Alex Graudenzi, Daniele Ramazzotti, et al.
Scientific Reports
|
May 23, 2017
Erratum: OncoScore: a novel, Internet-based tool to assess the oncogenic potential of genes
Rocco Piazza, Daniele Ramazzotti, Roberta Spinelli, et al.
Scientific Reports
|
April 8, 2017
OncoScore: a novel, Internet-based tool to assess the oncogenic potential of genes
Rocco Piazza, Daniele Ramazzotti, Roberta Spinelli, et al.
Nucleic Acids Research
|
July 10, 2025
Comprehensive analysis of mutational processes across 20 000 adult and pediatric tumors
Matteo Villa, Federica Malighetti, Luca De Sano, et al.
Nature Communications
|
September 25, 2023
Evolutionary signatures of human cancers revealed via genomic analysis of over 35,000 patients
Diletta Fontana, Ilaria Crespiatico, Valentina Crippa, et al.
Page
of 1
Search research articles
Search
Showing results (1-10 of 9) with videos related to
Sort By:
Page
of 1
BMC Bioinformatics
|
June 9, 2015
Automatising the analysis of stochastic biochemical time-series
Giulio Caravagna, Luca De Sano, Marco Antoniotti
BMC Bioinformatics
|
April 27, 2019
Learning mutational graphs of individual tumour evolution from single-cell and multi-region sequencing data
Daniele Ramazzotti, Alex Graudenzi, Luca De Sano, et al.
Proteomics
|
December 22, 2017
SIMLR: A Tool for Large-Scale Genomic Analyses by Multi-Kernel Learning
Bo Wang, Daniele Ramazzotti, Luca De Sano, et al.
Bioinformatics (Oxford, England)
|
February 11, 2016
TRONCO: an R package for the inference of cancer progression models from heterogeneous genomic data
Luca De Sano, Giulio Caravagna, Daniele Ramazzotti, et al.
Proceedings of the National Academy of Sciences of the United States of America
|
July 1, 2016
Algorithmic methods to infer the evolutionary trajectories in cancer progression
Giulio Caravagna, Alex Graudenzi, Daniele Ramazzotti, et al.
Scientific Reports
|
May 23, 2017
Erratum: OncoScore: a novel, Internet-based tool to assess the oncogenic potential of genes
Rocco Piazza, Daniele Ramazzotti, Roberta Spinelli, et al.
Scientific Reports
|
April 8, 2017
OncoScore: a novel, Internet-based tool to assess the oncogenic potential of genes
Rocco Piazza, Daniele Ramazzotti, Roberta Spinelli, et al.
Nucleic Acids Research
|
July 10, 2025
Comprehensive analysis of mutational processes across 20 000 adult and pediatric tumors
Matteo Villa, Federica Malighetti, Luca De Sano, et al.
Nature Communications
|
September 25, 2023
Evolutionary signatures of human cancers revealed via genomic analysis of over 35,000 patients
Diletta Fontana, Ilaria Crespiatico, Valentina Crippa, et al.
Page
of 1