Luca Alessandri
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Explore the profile of Luca Alessandri including associated specialties, affiliations and a list of published articles.
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21
Citations
143
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Recent Articles
1.
Alessandri S, Ratto M, Rabellino S, Piacenti G, Contaldo S, Pernice S, et al.
BMC Bioinformatics
. 2024 Mar;
25(1):110.
PMID: 38475691
Background: The analysis of large and complex biological datasets in bioinformatics poses a significant challenge to achieving reproducible research outcomes due to inconsistencies and the lack of standardization in the...
2.
DAgostino A, Di Marco G, Rolfo M, Alessandri L, Marvelli S, Braglia R, et al.
Ecol Evol
. 2024 Feb;
14(2):e11053.
PMID: 38405407
Plants have always represented a key element in landscape delineation. Indeed, plant diversity, whose distribution is influenced by geographic/climatic variability, has affected both environmental and human ecology. The present contribution...
3.
Arigoni M, Ratto M, Riccardo F, Balmas E, Calogero L, Cordero F, et al.
Sci Data
. 2024 Feb;
11(1):159.
PMID: 38307867
Single-cell RNA sequencing (scRNA-seq) has emerged as a vital tool in tumour research, enabling the exploration of molecular complexities at the individual cell level. It offers new technical possibilities for...
4.
Romboni M, Arienzo I, Di Vito M, Lubritto C, Piochi M, Di Cicco M, et al.
PLoS One
. 2023 Jul;
18(7):e0288637.
PMID: 37494366
This study focuses on the changes in diet and mobility of people buried in the La Sassa cave (Latium, Central Italy) during the Copper and Bronze Ages to contribute to...
5.
Pernice S, Sirovich R, Grassi E, Viviani M, Ferri M, Sassi F, et al.
Bioinformatics
. 2023 Apr;
39(5).
PMID: 37079732
Motivation: The transition from evaluating a single time point to examining the entire dynamic evolution of a system is possible only in the presence of the proper framework. The strong...
6.
Contaldo S, Alessandri L, Colonnelli I, Beccuti M, Aldinucci M
Methods Mol Biol
. 2022 Dec;
2584:337-345.
PMID: 36495459
The idea behind novel single-cell RNA sequencing (scRNA-seq) pipelines is to isolate single cells through microfluidic approaches and generate sequencing libraries in which the transcripts are tagged to track their...
7.
Mandreoli P, Alessandri L, Calogero R, Tangaro M, Zambelli F
Methods Mol Biol
. 2022 Dec;
2584:311-335.
PMID: 36495458
rCASC is a modular workflow providing an integrated environment for single-cell RNA-seq (scRNA-Seq) data analysis exploiting Docker containers to achieve functional and computational reproducibility. It was initially developed as an...
8.
Ratto M, Alessandri L
Methods Mol Biol
. 2022 Dec;
2584:251-268.
PMID: 36495455
An important point of the analysis of a single-cell RNA experiment is the identification of the key elements, i.e., genes, characterizing each cell subpopulation cluster. In this chapter, we describe...
9.
Alessandri L, Calogero R
Methods Mol Biol
. 2022 Dec;
2584:231-240.
PMID: 36495453
Single-cell RNA sequencing (scRNA-seq) allows for the creation of large collections of individual cells transcriptome. Unsupervised clustering is an essential element for the analysis of these data, and it represents...
10.
Avesani S, Viesi E, Alessandri L, Motterle G, Bonnici V, Beccuti M, et al.
Gigascience
. 2022 Aug;
11.
PMID: 35946989
Background: Spatial transcriptomics (ST) combines stained tissue images with spatially resolved high-throughput RNA sequencing. The spatial transcriptomic analysis includes challenging tasks like clustering, where a partition among data points (spots)...