StaffFilippo Biscarini


Informations



E-mail
biscarini@ibba.cnr.it

Office
Milano

Research area
BIOTEC, QUALY, BIOGEN


ORCID: 0000-0002-3901-2354
Google Scholar: Profile
Research Gate: Filippo Biscarini
Scopus Author: 25640857200

Biscarini Filippo

Senior Researcher

Education

2018: Habilitation as Associate and Full Professor in Animal Breeding and Genetics; Habilitation as Associate Professor in Plant Breeding and Genetics (ASN)

2006 – 2010: Wageningen University, The Netherlands: Ph.D. in animal breeding & genomics

1999: University of Utrecht, The Netherlands, Erasmus Programme – Veterinary Epidemiology and Food Safety

1996 – 2002: University of Perugia, Italy, M.Sc. in Veterinary Medicine

Professional experience

2018–Present: Senior Research Scientist, CNR (National Council for Research), Milan, Italy. Research in biostatistics, bioinformatics, plant and animal breeding, human medicine, machine learning and data analysis (’omics data). Supervison of students (BSc, MSc, PhD). Coordination of research projects. Teaching.

2018– 2021: Seconded National Expert, ERCEA (European Research Council Executive Agency), Bruxelles, Belgium. Call coordination and data analysis team: evaluation and monitoring of ERC project proposals, coordination of scientific panels, statistical analysis of related data, tool development. Text mining and topic modelling for the automated processing of text data

2017 – 2018: Senior Biostatistician, Cardiff University (School of Medicine), Cardiff, United Kingdom: One-year Marie-Curie fellowhip to carry out research on bioinformatics and biostatistics on autoimmune conditions (i.e. Graves’ disease and orbitopathy, celiac disease) in human patients. Analysis of ’omics data (RNA-sequencing, proteomics, metabolomics, metagenomics) and clinical features.

2016 – 2018: Research Scientist (Ricercatore III livello), CNR (National Council for Research), Milan, Italy: Research in biostatistics, bioinformatics, plant and animal breeding, human medicine, machine learning and data analysis (’omics data). Supervison of students (BSc, MSc, PhD). Coordination of research projects.

2017: IAEA Expert Mission, Centre national de la recherche appliquée au développement rural, Antananarivo, Madagascar: UN-IAEA mission to carry out a 5-days training course for local researchers and technicians (in French) on “Animal Identification, Recording Phenotypes and Performance Data to Enhance Cattle Breeding in Madagascar”.

2016: Researcher (RTD – tipo B), Università degli Studi di Teramo (School of Biosciences), Teramo, Italy: Research in Animal Breeding & Genetics, Biostatistics and Bioinformatics. Teaching animal breeding & genetics.

2014 – 2016: Principal Investigator, PTP Science Park, Lodi, Italy: Biostatistics and bioinformatics for the analysis of NGS (Next Generation Sequencing) data in animal, plant and human projects. Scientific coordination of national and international research projects. Coordinating a research group of 2/3 persons. Supervision of PhD and Master students.

2016: COST Short Term Scientific Mission, IRTA (Institut de Recerca i Tecnologia Agroalimentàries), Caldes de Montbui, Spain: COST Methagene Short-Term Scientific Mission to work on Bayesian statistical analysis of rumen methane emissions data in cattle.

2011 – 2014: Marie-Curie post-doctoral researcher, PTP Science Park, Lodi, Italy: Research on plant (sugar beet, rice, peach) and animal (sheep, cattle, goats, buffalo) statistical genetics, genomics and bioinformatics. Teaching statistics, programming and genetics courses. Supervision of PhD students.

2013: ESF Visiting Scientist, Cardiff University (School of Biosciences), Cardiff, UK: ESF (European Science Foundation) Grant to work on the genetic adaptation of animals to the environment.

2010 – 2011: Post-doctoral researcher, Georg-August Universität, Göttingen, Germany: Research on genomic predictions and selection in cattle. Teaching statistics. Supervision of PhD students.

2006 – 2010: Marie-Curie Phd fellow, Wageningen University, Wageningen, The Netherlands: Research on quantitative genetics and statistical genomics in laying hens. Assistant teacher in the master course “Animal breeding and genetics”. Supervision of master students.

2009 – 2010,:Secondary school trainee teacher, Vwo – Havo school ’t Hooghe Landt, Amersfoort, The Netherlands: Project “Becoming a teacher”: training in teaching in secondary schools and classes given under the supervision of a regular teacher. The subject of teaching was biology and the language dutch.

2003 – 2006: Quantitative Geneticist, Italian Holstein Association, Cremona, Italy: Routine genetic evaluation of dairy cattle. Research on dairy cattle quantitative genetics.

2005: Visiting scientist, University of Guelph, Guelph, Canada: Research project on selection index theory and breeding schemes in dairy cattle.

2002: Web-programmer, ICBF (Irish Cattle Breeders Federation), Cork, Ireland: Web-programmer, database analyst and trainee in quantitative genetics.

Research interests

  • Plant & animal breeding
  • Bioinformatics and biostatistics applications in plant & animal science and human medicine
  • Application of novel data analysis techniques and paradigms, namely machine-learning and deep learning combined with big data and distributed computing, to a large array of diverse biological problems
  • Genomic and multi-omics predictions
  • Alternative and complemetary methods for GWAS
  • Methods and tools for the imputation of missing data (genotypes, phenotypes)
  • Processing and analysis of big data (distributed computing, feature selection/creation, tool development)
  • Effect of noise (errors in the data) on omics predictions
  • Methods and applications for metagenomics in plants, animals, humans, model species.

Projects in progress

POLYPLOIDBREEDING 4.0: Expanding the toolbox for cereal breeding: high-throughput genomics, 2D-3D phenomics and artificial intelligence for breeding with increasing genome complexity, from barley to durum and bread wheat
Start date: 28/09/2023   End date: 27/09/2025

MIUR

Milano   Website

Filippo Biscarini

Project duration:
28/09/2023 - 27/09/2025
Financing body:
MIUR
Project research leader:
Filippo Biscarini
Headquarters:
Milano
Project website:
Website

POLYPLOIDBREEDING 4.0: Expanding the toolbox for cereal breeding: high-throughput genomics, 2D-3D phenomics and artificial intelligence for breeding with increasing genome complexity, from barley to durum and bread wheat


The project will focus on technology-driven breeding methods for the genetic improvement of crops (breeding 4.0) in diploid (barley, Hordeum vulgare) and polyploid (durum and bread wheat, Triticum durum, aestivum) species to increase cereal production in a sustainable and climate-smart way. Target technologies are high throughput phenotyping (e.g. drone phenotyping, root scans from rhizotrons) and genotyping (e.g. SNP array, exome sequencing, GBS) for artificial intelligence based breeding. Phenotypes will include yield, morphometric measurements, UAV (unmanned aerial vehicle: drone)-captured image data linked to morphology and production efficiency and rhizotron-based root scans (both 2D and 3D). Machine-learning methods, focussing especially on deep learning methods, will be used for phenomic and whole-genome predictions of target phenotypes.

Sheep-TreeSeq: Analisi scalabile della diversità genetica ovina usando alberi (grafi) di sequenze genomiche
Start date: 01/12/2023   End date: 30/11/2025

CNR/Royal Society (Biennio 2024-2025)

Milano
Filippo Biscarini

Project duration:
01/12/2023 - 30/11/2025
Financing body:
CNR/Royal Society (Biennio 2024-2025)
Project research leader:
Filippo Biscarini
Headquarters:
Milano

Sheep-TreeSeq: Analisi scalabile della diversità genetica ovina usando alberi (grafi) di sequenze genomiche


Sheep-TreeSeq will perform scalable analysis of genomic diversity of sheep global populations using the novel tree sequence data format and methodology.

Technological advances in agritech have increased the availability of genomic data, leading to massive datasets (“big data”) which pose challenges for storage, processing and analysis, e.g. the sheer volume of the data, the rapid generation of new data (updating results, expanding training populations, streaming applications), and the heterogeneity of data sources (integration of data from multiple sequencing and genotyping platforms). The tree sequence algorithm offers an excellent way to address such challenges, by providing lossless compression and novel representation of the data. As an example, using tree sequences on the 1000 Bull Genome Project data a 90% lossless compression was obtained, reducing the data size from ~800 GB to 45 GB. For the Sheep TreeSeq project we will use around 3,500 sheep whole genome sequences and over 50,000 genotypes (~10 TB of data).

Our plan is to apply the tree sequence approach to compress the data and obtain a data representation highly suited for population genetics and demographic analysis: (i) principal component and genealogical nearest neighbour clustering; (ii) fixation index measuring genetic differentiation; (iii) deep neural network based clustering methods; iv) detection of runs of homozygosity (ROH) and heterozygosity-rich regions (HRR).

This is the first time that this approach is applied to sheep genomics.

Projects completed

FREECLIMB - Fruit Crops Resilience to Climate Change in the Mediterranean Basin
Start date: 01/04/2019   End date: 27/03/2023

Unione Europea

Milano   Website

Filippo Biscarini

Project duration:
01/04/2019 - 27/03/2023
Financing body:
Unione Europea
Project research leader:
Filippo Biscarini
Headquarters:
Milano
Project website:
Website

FREECLIMB - Fruit Crops Resilience to Climate Change in the Mediterranean Basin


The FREECLIMB project is built to match topic 1.2.1 of the PRIMA (Sect. 2) framework in developing smart and sustainable farming systems in Mediterranean countries, to preserve natural resources (water and land use) by increasing production efficiency. This will be pursued by advancing knowledge on mechanisms of plant environmental adaptation and biotic/abiotic stress resilience. The project targets major fruit tree species with the aim of improving the availability of breeding and germplasm material adapted to limited external resources (input) and future climatic scenarios predicted for the Mediterranean area, through the characterization and exploitation of local biodiversity. The project will focus on key ideotypes elaborated in collaboration with Fruit Farming Actors (FFAs, breeders, nurseries, growers) with the core objective of providing a toolkit (diverse germplasm, tools and methods) to accelerate exploitation, breeding and selection of resilient varieties in key traditional fruit crops of Mediterranean agriculture (stone fruits such as peach, apricot and almond; Citrus spp.; grape and olive).
RABoLa - Sustainable strategies to reduce the use of antibiotics in dairy farming
Start date: 28/12/2018   End date: 27/06/2022

Regione Lombardia

Milano, Lodi   Website

Paola Cremonesi, Laura Morello

Project duration:
28/12/2018 - 27/06/2022
Financing body:
Regione Lombardia
Project research leader:
Paola Cremonesi, Laura Morello
Headquarters:
Milano, Lodi
Project website:
Website

RABoLa - Sustainable strategies to reduce the use of antibiotics in dairy farming


The project, which involves different departments of the University of Milan (DISAA, DIMEVET, VESPA), researchers from the CNR ISPA and CNR IBBA and the DIANA Department of the Catholic University of the Sacred Heart of Piacenza, aims the primary identification of operative practices for reducing the use of antibiotics in the dairy cow herds. During the study, operative protocols already preliminary tested (administration of Aloe arborescens, use of Lactococcus lactis subsp. cremoris in pre and post dipping, molecules to inhibit Prototheca spp) will be validated during the entire lactation cycle of the cows.

This project will allow breeders to take advantages of new nutraceutical strategies and alternatives to the use of antibiotics, to enhance the innate defences and reduce the incidence and severity of mastitis. The validation of an effective protocol for the selective drying of animals would lead to a reduction of the preventive use of antibiotics, in line with what is requested at European level.

FARM-INN Farm-level interventions supporting dairy industry innovation
Start date: 05/10/2020   End date: 31/08/2021

AGER

Lodi   Website

Bianca Castiglioni

Project duration:
05/10/2020 - 31/08/2021
Financing body:
AGER
Project research leader:
Bianca Castiglioni
Headquarters:
Lodi
Project website:
Website

FARM-INN Farm-level interventions supporting dairy industry innovation


The project FARM-INN aims to provide farm-level interventions supporting dairy industry enhancing safety and quality of milk and cheese and providing the necessary scientific evidence and new insight regarding their functional properties. The proposed actions will be carried out assessing and improving animal welfare and the environmental sustainability. In particular, two aspects will be tackled and studied in the proposed project: i) the development and use of new feed supplements adsorbing mycotoxins and reducing pathogenic and spoilage clostridia in milk ii) the characterization of cheese making and functional properties of A1 and A2 variants of beta-casein in milk. The evaluation of environmental sustainability of the adsorbent supplementations to the cow rations and the potential effect of cheese making using A1 and A2 beta-casein types in milk analyses through a Life Cycle Assessment approach will be performed.

The project will offer opportunities to the dairy farmers to strengthen their competitiveness, in the context of a better control of safety and quality issues, and will help dairy industry in placing on the market high-quality products adapted to the new expectations of consumers.

USEFUL - Development of techniques and supply chain processes (farms and dairies) to optimize environmental, territorial and managerial factors aimed at obtaining greater production efficiency and qualitative excellence in the production of DOP and typical cheeses
Start date: 18/12/2019   End date: 17/06/2023

Regione Lombardia

Milano, Lodi   Website

Bianca Castiglioni

Project duration:
18/12/2019 - 17/06/2023
Financing body:
Regione Lombardia
Project research leader:
Bianca Castiglioni
Headquarters:
Milano, Lodi
Project website:
Website

USEFUL - Development of techniques and supply chain processes (farms and dairies) to optimize environmental, territorial and managerial factors aimed at obtaining greater production efficiency and qualitative excellence in the production of DOP and typical cheeses


The USEFUL project aims to solve some critical issues in the production of Lombardy PDO cheeses (Grana Padano and Taleggio) in order to guarantee the competitiveness of the agro-industry companies. To this end, supply chain strategies and operational tools will be developed that allow to improve the microbiological and cheese-making quality of the milk and to improve all the cheese-making processes. These objectives will be achieved through the integration of the 3 sub-projects: Coordination, Innovation and Technological Transfer.

The expected results are: 1) to identify new procedures to improve animal health, food safety and the microbiological quality and cheese-making properties of milk; 2) to identify innovative procedures and operational tools to be used in the dairy industry to monitor the cheese-making and maturing phases of the cheese; 3) to define guidelines, technical manuals and fact sheets on the various procedures and techniques.

Istituto

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