NEWS

- EDITORIAL NEWS

-- Traditional and Machine Learning Methods to Solve Imaging Problems, Section Collection of Algorithms. Open for submissions.

-- Algorithms for Biomedical Image Analysis and Processing, Special Issue of Algorithms, 2023. See the Editorial.


- RECENT PUBLICATIONS and SOFTWARE/DATA

-- L. Maddalena and L. Antonelli (Eds), Algorithms for Biomedical Image Analysis and Processing, Reprint of the Special Issue, Algorithms, ISBN: 978-3-0365-9760-7, DOI: 10.3390/books978-3-0365-9761-4, 2024.

-- M. Giordano, E. Falbo, L. Maddalena, M. Piccirillo, I. Granata, Untangling the Context-Specificity of Essential Genes by Means of Machine Learning: A Constructive Experience, Biomolecules 14(1), ISSN: 2218-273X, DOI: 10.3390/biom14010018, 2024. Data available here.

-- L. Antonelli, L. Maddalena, Special Issue on "Algorithms for Biomedical Image Analysis and Processing", Algorithms 16(12), Editorial, DOI: 10.3390/a16120544, 2023.

-- L. Antonelli, F. Polverino, A. Albu, A. Hada, I.A. Asteriti, F. Degrassi, G. Guarguaglini, L. Maddalena, M.R. Guarracino, ALFI: Cell cycle phenotype annotations of label-free time-lapse imaging data from cultured human cells, Scientific Data 10(677), DOI: 10.1038/s41597-023-02540-1, 2023. The ALFI dataset is available here.

-- I. Granata, M. Giordano, L. Maddalena, M. Manzo, M.R. Guarracino, Network-Based Computational Modeling to Unravel Gene Essentiality, in R.P. Mondaini (Ed), Trends in Biomathematics: Modeling Epidemiological, Neuronal, and Social Dynamics. BIOMAT 2022. Springer, Cham, DOI: 10.1007/978-3-031-33050-6_3, 2023.

-- Khachatryan, L., Xiang, Y., Ivanov, A. et al., Results and lessons learned from the sbv IMPROVER metagenomics diagnostics for inflammatory bowel disease challenge, Scientific Reports 13, 6303 DOI: 10.1038/s41598-023-33050-0, 2023.

-- M. Manzo, M. Giordano, L. Maddalena, M.R. Guarracino, I. Granata, Novel Data Science Methodologies for Essential Genes Identification Based on Network Analysis, In Dzemyda, G., Bernataviciene, J., Kacprzyk, J. (eds), Data Science in Applications. Studies in Computational Intelligence, Vol. 1084, Springer, Cham., DOI: 10.1007/978-3-031-24453-7_7, 2023. Related software and data available here.

-- L. Maddalena, I. Granata, M. Giordano, M. Manzo, M.R. Guarracino, Integrating Different Data Modalities for the Classification of Alzheimer's Disease Stages, SN Computer Science, vol. 4, no. 249, DOI: 10.1007/s42979-023-01688-2, 2023. Related software and data available here. Free view-only version available here.

-- I. Manipur, M. Giordano, M. Piccirillo, S. Parashuraman and L. Maddalena, Community Detection in Protein-Protein Interaction Networks and Applications, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 20, no. 1, DOI: 10.1109/TCBB.2021.3138142, 2023. See also the Supplemental Material.

-- L. Maddalena, M. Giordano, M. Manzo, M.R. Guarracino, Whole-Graph Embedding and Adversarial Attacks for Life Sciences, in R.P. Mondaini (Ed), Trends in Biomathematics: Stability and Oscillations in Environmental, Social, and Biological Models: Selected Works from the BIOMAT Consortium Lectures, Rio de Janeiro, Brazil, 2021, Springer International Publishing, DOI: 10.1007/978-3-031-12515-7_1, 1--21, 2022.

-- I. Granata, I. Manipur, M. Giordano, L. Maddalena, M.R. Guarracino, TumorMet: A repository of tumor metabolic networks derived from context-specific Genome-Scale Metabolic Models, Scientific Data, DOI: 10.1038/s41597-022-01702-x, vol. 9, no. 607, 2022. See the TumorMet repository.

-- M. Giordano, L. Maddalena, M. Manzo, M.R. Guarracino, Adversarial attacks on graph-level embedding methods: a case study, Ann Math Artif Intell, DOI: 10.1007/s10472-022-09811-4, 2022. Free view-only version available here.

-- L. Maddalena, L. Antonelli, A. Albu, A. Hada, M.R. Guarracino, Artificial Intelligence for Cell Segmentation, Event Detection, and Tracking for Label-free Microscopy Imaging, Algorithms, DOI: 10.3390/a15090313, vol. 15, no. 313, 2022.

-- I. Manipur, M. Manzo, I. Granata, M. Giordano, L. Maddalena, and M.R. Guarracino, Netpro2vec: a Graph Embedding Framework for Biomedical Applications , in IEEE/ACM Transactions on Computational Biology and Bioinformatics, DOI: 10.1109/TCBB.2021.3078089, vol. 19, no. 2, 2022. Related software available here.

-- L. Maddalena, I. Granata, M. Giordano, M. Manzo, M.R. Guarracino, and for the Alzheimer's Disease Neuroimaging Initiative, Classifying Alzheimer's Disease Using MRIs and Transcriptomic Data, Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: BIOIMAGING, ISBN 978-989-758-552-4, ISSN 2184-4305, DOI: 10.5220/0010902900003123, pages 70-79, 2022.

Lucia Maddalena

- ORCID: ORCID iD iconorcid.org/0000-0002-0567-4624

- Scopus Author ID: 9735344700

- WoS Researcher ID: K-5508-2013

- Google Scholar: Lucia_Maddalena

- SciProfiles: 422781

- Loop Profiles: 1482549

Positions:

- Senior Researcher, National Research Council (CNR), Institute for High-Performance Computing and Networking (ICAR), Naples Branch

- Director, ICAR-CNR INdAM Research Unit

- Scientific Coordinator, ICAR-CNR Computational Data Science group (CDS-group)

Mailing Address:

Lucia Maddalena

ICAR-CNR, Naples Branch

Via P. Castellino 111, 80131 Naples, Italy

Tel.: +39 081 6139522

Fax: +39 081 6139531

lucia.maddalena 'at' cnr.it


Last update: February 28, 2024