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PRIN 2022 PNRR Project:Computational approaches for the integration of multi-omics data (2022BLN38)

  1. This project is funded by European Union - Next Generation EU, within the PRIN 2022 PNRR program (D.D. 1409 del 14/09/2022 Ministero dell’Università e della Ricerca) within the PRIN 2022 PNRR call - Decreto Direttoriale n. 1409 del 14-9-2022 Ministero dell’Università e della Ricerca.
  2. (CUP B53D23027810001)

  1. The project involves two research units at UniBA and at IAC-CNR , respectively.
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  3. The UniBA unit leads the project.
  4. The Project Team comprises a diverse mix of early-stage and senior researchers led by two women ( Prof. Del Buono at the UniBA unit and Dr. Angelini at the IAC-CNR unit).
  5. Prof. Del Buono will act as the project PI, and Dr. Angelini will be the Associated PI.


    6. Important dates

  6. The project officially started on November 30, (2023) and will last for 24 Months.

AIMS

    This project aims to:
  1. Aim 1: Develop novel computational methods for multi-omics data integration,
  2. Aim 2: Release open-source packages implementing the proposed methodologies,
  3. Aim 3: Use the proposed methodologies (together with existing approaches) to analyze case studies in cell development and cancer,
  4. Aim 4: Disseminate and discuss within the scientific community the proposed approaches and the findings emerging from the analysis of the case study.
    5. .

Work Packages

  1. WP1: Unsupervised data integration methods (Months 1-18 - Leader UniBA)
  2. WP2: Supervised data integration methods (Months 1-18 - Leader IAC-CNR)
  3. WP3: Packages implementation (Months 12-24 - Leader IAC-CNR)
  4. WP4: Applications to case studies and benchmarking in the literature (Months 12-24 - Leader UniBA)
  5. WP5: Dissemination (Months 12-24 - Leader UniBA)

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IAC-CNR Participants

  1. C. Angelini, Head of the IAC-CNR Unit.
  2. A. Raiconi IAC-CNR Research staff.

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Open/Closed Calls at IAC CNR

  1. 1. Bando IAC-04-2024-NA, PUBBLICA SELEZIONE PER IL CONFERIMENTO DI N° 2 ASSEGNI PER LO SVOLGIMENTO DI ATTIVITÀ DI RICERCA NELL’AMBITO DEL PROGRAMMA DI RICERCA FINANZIATO DALL’UNIONE EUROPEA-NEXT GENERATION EU “PROGETTI PRIN 2022 PNRR”, SETTORE PE1, P2022BLN38 - “COMPUTATIONAL APPROACHES FOR THE INTEGRATION OF MULTI-OMICS DATA”. CUP B53D23027810001. Deadline for applications 1/10/2024
  2. 2. Bando IAC-02-2024-NA PUBBLICA SELEZIONE PER IL CONFERIMENTO DI N° 1 ASSEGNO PER LO SVOLGIMENTO DI ATTIVITÀ DI RICERCA NELL’AMBITO DEL PROGRAMMA DI RICERCA FINANZIATO DALL’UNIONE EUROPEA-NEXT GENERATION EU “PROGETTI PRIN 2022 PNRR”, SETTORE PE1, P2022BLN38 - “COMPUTATIONAL APPROACHES FOR THE INTEGRATION OF MULTI-OMICS DATA”. CUP B53D23027810001. Deadline for applications 10/7/2024

IAC-CNR Results

Open Access Publications

  1. 1. C. Angelini, D. De Canditiis, I. De Feis, A. Iuliano. A network-constrain Weibull AFT model for biomarkers discovery Biometrical Journal, 66 (7), e202300272, (2024).
  2. 2. V. Policastro, M. Magnani, C. Angelini, A. Carissimo. INet for network integration , Computational Statistics (2024).

Open Source Software

  1. 1. AFTNet The R package AFTNet implements a novel network-constraint survival analysis method based on the Weibull accelerated failure time (AFT). (2024).
  2. 2. INet-Tool The R package INetTool implements the network integration algorithm and contains other additional routines valid for pre or post-analysis. (2024).

Conference Presentations

  1. 1. C. Angelini, D. De Canditiis, I. De Feis, A. Iuliano AFTNet: a novel network-penalized Weibull AFT regression algorithm and its applications to cancer survival., SIS meeting 2024, Bari, 20/06/2024.