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Information on didactic, research and institutional assignments on this page are certified by the University; more information, prepared by the lecturer, are available on the personal web page and in the curriculum vitae indicated on this webpage.
Information
LecturerMasseroli Marco
QualificationAssociate professor full time
Belonging DepartmentDipartimento di Elettronica, Informazione e Bioingegneria
Scientific-Disciplinary SectorIINF-05/A - Information Processing Systems
Curriculum VitaeDownload CV (310.42Kb - 11/04/2024)
OrcIDhttps://orcid.org/0000-0003-2574-1174

Contacts
Office hours
DepartmentFloorOfficeDayTimetableTelephoneFaxNotes
Elettronica e Informazione ------TuesdayFrom 14:45
To 16:15
02-2399-3553---The best interaction modality is by email, also to agreed on and reserve meetings
E-mailmarco.masseroli@polimi.it
Personal websitehttp://www.bioinformatics.polimi.it/masseroli/

Data source: RE.PUBLIC@POLIMI - Research Publications at Politecnico di Milano

List of publications and reserach products for the year 2024 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Contributions on scientific books
Biological and Medical Ontologies: Disease Ontology (DO) (Show >>)


List of publications and reserach products for the year 2023 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Abstract in Atti di convegno
Adapting feature selection in gene expression-based classification for higher biological interpretability (Show >>)
Gene co-expression network analysis for identifying cell populations in RNA-seq patient-derived xenografts (Show >>)
Machine learning for multi-label subtyping: a key to dissecting intra-tumor heterogeneity at the bulk sample level (Show >>)
Multi-label transcriptional classification of colorectal cancer reflects tumour cell population heterogeneity (Show >>)
Multi-label transcriptional classification of colorectal cancer reflects tumour cell population heterogeneity (Show >>)
RAAVioli: a bioinformatic tool for the characterization of AAV integration and recombination processes (Show >>)
The use of machine learning in the genomic era of livestock farming (Show >>)
Transcriptional analysis of the synergistic mechanism of action of simvastatin and valproic acid with chemotherapy in metastatic pancreatic adenocarcinoma. (Show >>)
Unraveling the effect of proliferative stress in vivo in hematopoietic stem cell gene therapy (Show >>)
Use of longitudinal data in genomic management of dairy cattle herds (Show >>)
Conference proceedings
Biologically-driven feature selection for improved functional interpretability of gene expression data analysis (Show >>)
Non-negative Matrix Tri-Factorization for data integration and knowledge inference on breast cancer subtyping (Show >>)
Journal Articles
Identification of transcription factor high accumulation DNA zones (Show >>)
Multi-label transcriptional classification of colorectal cancer reflects tumor cell population heterogeneity (Show >>)
Supervised Relevance-Redundancy assessments for feature selection in omics-based classification scenarios (Show >>)
The ENCODE Imputation Challenge: a critical assessment of methods for cross-cell type imputation of epigenomic profiles (Show >>)


List of publications and reserach products for the year 2022 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Abstract in Atti di convegno
Gene expression-based multi-label classification to face colorectal cancer heterogeneity and provide biologically and clinically relevant traits (Show >>)
Statistical and machine learning methods to investigate mutations in RAS-mutated colorectal cancer patients (Show >>)
Conference proceedings
An integrated, scalable framework for identification and quantification of tandem duplications in DNA sequencing data (Show >>)
Machine learning to discover genes predictive of RAS-mutated cases in mutational profiles of colorectal cancer patients. (Show >>)
Journal Articles
Accurate and highly interpretable prediction of gene expression from histone modifications (Show >>)
Genomic data integration and user-defined sample-set extraction for population variant analysis (Show >>)
Identification, semantic annotation and comparison of combinations of functional elements in multiple biological conditions (Show >>)
Investigating Deep Learning based Breast Cancer Subtyping using Pan-cancer and Multi-omic Data (Show >>)
META-BASE: a Novel Architecture for Large-Scale Genomic Metadata Integration (Show >>)
Predicting Drug Synergism by Means of Non-Negative Matrix Tri-Factorization (Show >>)
RGMQL: scalable and interoperable computing of heterogeneous omics big data and metadata in R/Bioconductor (Show >>)


List of publications and reserach products for the year 2021 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Conference proceedings
A novel computational framework for the identification of the TD-plus phenotype in high grade serous ovarian cancer (Show >>)
Investigating transcript isoform RNA-seq data and machine learning techniques for breast cancer subtyping (Show >>)
Journal Articles
A review on viral data sources and search systems for perspective mitigation of COVID-19 (Show >>)
Computational analysis of fused co-expression networks for the identification of candidate cancer gene biomarkers (Show >>)
Federated sharing and processing of genomic datasets for tertiary data analysis (Show >>)
Gene function finding through cross-organism ensemble learning (Show >>)
Predictive modeling of gene expression regulation (Show >>)
Supervised machine learning for the assessment of Chronic Kidney Disease advancement (Show >>)
The road towards data integration in human genomics: players, steps and interactions (Show >>)


List of publications and reserach products for the year 2020 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Contributions on scientific books
Evaluating Deep Semi-supervised Learning for Whole-Transcriptome Breast Cancer Subtyping (Show >>)
Exposing and characterizing subpopulations of distinctly regulated genes by k-plane regression (Show >>)
Network modeling and analysis of normal and cancer gene expression data (Show >>)
Conference proceedings
Boosting perspectives for breast cancer intrinsic subtyping on RNA-sequencing data (Show >>)
Hybrid evolutionary framework for selection of genes predicting breast cancer relapse (Show >>)
Journal Articles
Association rule mining to identify transcription factor interactions in genomic regions (Show >>)
Machine learning for RNA sequencing-based intrinsic subtyping of breast cancer (Show >>)
Matrix Factorization-based Technique for Drug Repurposing Predictions (Show >>)
OpenGDC: Unifying, Modeling, Integrating Cancer Genomic Data and Clinical Metadata (Show >>)
SMfinder: Small molecules finder for metabolomics and lipidomics analysis (Show >>)
Search and comparison of (epi)genomic feature patterns in multiple genome browser tracks (Show >>)
manifesti v. 3.7.1 / 3.7.1
Area Servizi ICT
13/07/2024