Giacomo Baruzzo

muxvizpy: a Python library for the analysis of multilayer biological networks

matteo baldan, Francesco Zambelli, Andrea Valsecchi, Giacomo Baruzzo et autres

Biological systems are inherently multilayered: the same entities---genes, cells, or bacterial species---participate simultaneously in qualitatively distinct types of interactions, each carrying complementary information that no single relational view can capture. Analysing such systems with single-layer tools, or by collapsing layers into a …

muxvizpy: a Python library for the analysis of multilayer biological networks

matteo baldan, Francesco Zambelli, Andrea Valsecchi, Giacomo Baruzzo et autres

Biological systems are inherently multilayered: the same entities---genes, cells, or bacterial species---participate simultaneously in qualitatively distinct types of interactions, each carrying complementary information that no single relational view can capture. Analysing such systems with single-layer tools, or by collapsing layers into a …

it (code pays fourni par la source)

NEBULA: A scalable and efficient framework for SNP-set analysis in the era of whole genome sequencing

Mikele Milia, Giacomo Baruzzo, Barbara Di Camillo

Understanding the role of genetic variants in complex diseases is central to modern genomics. Genome-wide association and whole genome sequencing studies enable genotype-phenotype association discovery, but the growing scale of datasets poses computational challenges. Single nucleotide polymorphism set (SNP-set) analysis methods, which …

it (code pays fourni par la source)

MOV&RSim: computational modelling of cancer-specific variants and sequencing reads characteristics for realistic tumoral sample simulation

Francesca Longhin, Giacomo Baruzzo, Enidia Hazizaj, D. Boscarino et autres

BACKGROUND: Bioinformatics pipelines for variant calling have undergone significant advancements due to the decreasing costs of next-generation sequencing. Accurate mutation detection is crucial for personalised medicine in cancer, particularly in assignment of therapy. Somatic variant calling, however, remains challenging due to diverse …

it (code pays fourni par la source)

Biologically Informed procedure for Feature Summarization in Spatial Transcriptomics

Giulia Cesaro, Giacomo Baruzzo, Barbara Di Camillo

Modern machine learning approaches have shown remarkable success in extracting patterns from high-dimensional biological data. However, when applied to spatial transcriptomics, these methods face significant challenges due to the sparsity of spatially resolved measurements and the complex, nonlinear relationships between molecular features.To …

it (code pays fourni par la source)

Advances and challenges in cell–cell communication inference: a comprehensive review of tools, resources, and future directions

Giulia Cesaro, James S. Nagai, Nicolò Gnoato, Alice Chiodi et autres

Recent advancements in high-resolution and high-throughput sequencing technologies have significantly enhanced the study of cell-cell communication inference using single-cell and spatial transcriptomics data. Over the past 6 years, this growing interest has led to the development of more than 100 bioinformatics tools …

it, de, us (code pays fourni par la source)

Differential cellular communication inference framework for large-scale single-cell RNA-sequencing data

Giulia Cesaro, Giacomo Baruzzo, Gaia Tussardi, Barbara Di Camillo

Single-cell transcriptomics data have been widely used to characterize biological systems, particularly in studying cell-cell communication, which plays a significant role in many biological processes. Despite the availability of various computational tools for inferring cellular communication, quantifying variations across different experimental conditions …

it (code pays fourni par la source)

quickSparseM: a library for memory- and time-efficient computation on large, sparse matrices with application to omics data

Giacomo Baruzzo, Giulia Cesaro, Barbara Di Camillo

Omics data have revolutionized molecular biology by introducing large-scale data analysis, pushing the field into the realm of big data and presenting substantial challenges in data storage and analysis. Despite describing distinct aspects of molecular biology, most omics data share common characteristics, …

it (code pays fourni par la source)

Validity of Feature Importance in Low-Performing Machine Learning for Tabular Biomedical Data

Youngro Lee, Giacomo Baruzzo, Jeonghwan Kim, Jong-Mo Seo et autres

In tabular data analysis within biomedical research, achieving high model accuracy is often considered a prerequisite for discussing feature importance, as medical practitioners expect the validity of feature importance to correlate with model performance. In this work, we challenge this prevailing belief …

kr, it, us (code pays fourni par la source)

A standardised open science framework for sharing and re-analysing neural data acquired to continuous stimuli

Giovanni M. Di Liberto, Aaron Nidiffer, Michael J. Crosse, Nathaniel J. Zuk et autres

Neurophysiology research has demonstrated that it is possible and valuable to investigate sensory processing in scenarios involving continuous sensory streams, such as speech and music. Over the past 10 years or so, novel analytic frameworks combined with the growing participation in data …

ca, ie, us, gb, it (code pays fourni par la source)

Validity of Feature Importance in Low-Performing Machine Learning for Tabular Biomedical Data

Youngro Lee, Giacomo Baruzzo, Jeonghwan Kim, Jong-Mo Seo et autres

In tabular biomedical data analysis, tuning models to high accuracy is considered a prerequisite for discussing feature importance, as medical practitioners expect the validity of feature importance to correlate with performance. In this work, we challenge the prevailing belief, showing that low-performing …

A standardised open science framework for sharing and re-analysing neural data acquired to continuous stimuli

Giovanni M. Di Liberto, Aaron Nidiffer, Michael J. Crosse, Nathaniel J. Zuk et autres

Neurophysiology research has demonstrated that it is possible and valuable to investigate sensory processing in scenarios involving continuous sensory streams, such as speech and music. Over the past 10 years or so, novel analytic frameworks combined with the growing participation in data …