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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 GroupIINF-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 2026 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Abstract in Rivista
Cell-Free DNA Signatures as Non-Invasive Biomarkers of Disease Progression in Metachromatic Leukodystrophy (Show >>)
High-Resolution Analysis of AAV Integrations in Preclinical Gene Therapy Models using RAAVioli (Show >>)
New Frontiers in Genotoxicity Detection by Multiparametric Analyses for Gene Therapy (Show >>)
Oncogene activation by lentiviral vectors drives senescence linked clonal haematopoiesis and mutation accumulation in HSPC gene therapy (Show >>)
Journal Articles
Cross-Generational Validation of a Feedforward Neural Network for Milk Yield Prediction in Dairy Cattle (Show >>)
RAAVioli: A comprehensive approach to characterizing AAV vector integrations and rearrangements (Show >>)


List of publications and reserach products for the year 2025 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Abstract in Rivista
Cell-free DNA Profiling as a Non-Invasive Approach for Assessing CAR-T Therapy Outcomes and Toxicity (Show >>)
Characterization of AAV Integrations in preclinical models of gene therapy using RAAVioli pipeline with long and short sequencing reads (Show >>)
Exploring Cell-Free DNA Signatures as Biomarkers for Disease Progression in Metachromatic Leukodystrophy (Show >>)
Unravelling the effect of proliferative stress and genotoxicity in hematopoietic stem cells in vivo (Show >>)
Validation of life's simple 7 and life's essential 8 in a European cohort: the role of sleep in cardiovascular risk estimation (Show >>)
Vector insertional mutagenesis drives accelerated hematopoietic stem cell aging and acquisition of somatic mutations in vivo (Show >>)
Abstract in Atti di convegno
A deep learning representation of common genetic variants improves the prediction of coronary artery disease beyond polygenic risk scores (Show >>)
Dissecting interactome-driven subtypes of Colorectal Cancer (Show >>)
Enabling Cell-Free DNA Deconvolution Across Sequencing Depths Through Deep Neural Networks (Show >>)
Multi-modal integration reveals the joint role of electrocardiogram, imaging and genetics in cardiovascular risk (Show >>)
New Frontiers in Genotoxicity Detection by Multiparametric Analyses for Gene Therapy (Show >>)
VISMA: Vector Integration Site Mutation Analysis (Show >>)
Poster
A novel machine learning-based workflow to capture intra-patient heterogeneity through transcriptional multi-label characterization and clinically relevant classification (Show >>)
HR-SC: an academic-developed machine learning framework to classify HRD-positive ovarian cancer patients and predict sensitivity to olaparib. (Show >>)
Similarity Network Fusion for Clustering Incomplete Mixed-Type Data (Show >>)
Contributions on scientific books
Benchmark Study on Supervised Relevance-Redundancy Assessment for Feature Selection in Genomic Data (Show >>)
Biological and Medical Ontologies: Disease Ontology (DO) (Show >>)
Biological and Medical Ontologies: GO and GOA (Show >>)
Biological and Medical Ontologies: Human Phenotype Ontology (HPO) (Show >>)
Biological and Medical Ontologies: Introduction (Show >>)
Biological and Medical Ontologies: PRotein Ontology (PRO) (Show >>)
Enhancing Functional Interpretability in Gene Expression Analysis Through Biologically-Guided Feature Selection (Show >>)
Forward and Backward Feature Selection Guided by Prior Biological Knowledge for Enhanced Interpretability (Show >>)
Inferring Breast Cancer Subtype Associations Using an Original Omics Integration Based on Non-negative Matrix Tri-Factorization (Show >>)
Integrative Bioinformatics (Show >>)
Performance Measures for Multi-Class Classification (Show >>)
Semi-Supervised Learning (Show >>)
Supervised Learning: Multi-Label Classification (Show >>)
Three-Stage Data Science Methodology to Explore Genetic Heterogeneity of Diseases (Show >>)
Conference proceedings
Conformal prediction in breast cancer subtype identification (Show >>)
Deep learning-based phenotyping of complex health data increases disease prediction power over traditional features (Show >>)
Generative AI for Gene Expression Profiles: A Biologically Informed Graph Neural Network Approach (Show >>)
Predicting Clinical Relapse in Takayasu Arteritis using [18F]FDG PET-based CNNs (Show >>)
Journal Articles
A novel machine learning-based workflow to capture intra-patient heterogeneity through transcriptional multi-label characterization and clinically relevant classification (Show >>)
BioGAN: Enhancing Transcriptomic Data Generation with Biological Knowledge (Show >>)
HR-SC—an academic-developed machine learning framework to classify HRD-positive ovarian cancer patients and predict sensitivity to olaparib (Show >>)
Machine learning-based forecast of Helmet-CPAP therapy failure in Acute Respiratory Distress Syndrome patients (Show >>)


List of publications and reserach products for the year 2024 (Show all details | Hide all details)
Type Title of the Publicaiton/Product
Abstract in Rivista
Acquisition of somatic mutations after hematopoietic stem cell gene therapy varies among cell lineages and is modulated by vector genotoxicity and the activity of key cellular senescence gene (Show >>)
Characterization of AAV Integrations in Preclinical Models of Gene Therapy Using RAAVioli Pipeline with Long and Short Sequencing Reads (Show >>)
Abstract in Atti di convegno
Biology-informed bulk RNA-seq profile generation (Show >>)
Diagnosis of cardiovascular diseases using interpretable cardiac magnetic resonance-derived latent factors (Show >>)
Prediction of incident cardiovascular events using omics-derived latent factors (Show >>)
Unraveling the effects of proliferative stress and genotoxicity in hematopoietic stem cells in vivo (Show >>)
Conference proceedings
A data science approach to investigate the mutational landscape of a critical patient subgroup (Show >>)
Enhancing feature selection with biological insights: a novel forward approach for gene selection (Show >>)
Journal Articles
Biologically weighted LASSO: enhancing functional interpretability in gene expression data analysis (Show >>)
In-Silico Identification of Novel Pharmacological Synergisms: The Trabectedin Case (Show >>)
Integrated approach to generate artificial samples with low tumor fraction for somatic variant calling benchmarking (Show >>)
Predicting bovine daily milk yield by leveraging genomic breeding values (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 >>)
manifesti v. 3.14.3 / 3.14.3
Area Servizi ICT
13/05/2026