Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Annalisa Occhipinti"'
Publikováno v:
Resilient Cities and Structures, Vol 3, Iss 1, Pp 20-43 (2024)
Traditionally, nonlinear time history analysis (NLTHA) is used to assess the performance of structures under future hazards which is necessary to develop effective disaster risk management strategies. However, this method is computationally intensive
Externí odkaz:
https://doaj.org/article/e2ae0a2f96374a84ade53c2d8e537203
Autor:
Suraj Verma, Giuseppe Magazzù, Noushin Eftekhari, Thai Lou, Alex Gilhespy, Annalisa Occhipinti, Claudio Angione
Publikováno v:
Cell Reports: Methods, Vol 4, Iss 7, Pp 100817- (2024)
Summary: Deep-learning tools that extract prognostic factors derived from multi-omics data have recently contributed to individualized predictions of survival outcomes. However, the limited size of integrated omics-imaging-clinical datasets poses cha
Externí odkaz:
https://doaj.org/article/32614dcd4ffc4c0a825eb02e99d3218f
Autor:
Maxime RF Gosselin, Virginie Mournetas, Malgorzata Borczyk, Suraj Verma, Annalisa Occhipinti, Justyna Róg, Lukasz Bozycki, Michal Korostynski, Samuel C Robson, Claudio Angione, Christian Pinset, Dariusz C Gorecki
Publikováno v:
eLife, Vol 11 (2022)
Duchenne muscular dystrophy (DMD) affects myofibers and muscle stem cells, causing progressive muscle degeneration and repair defects. It was unknown whether dystrophic myoblasts—the effector cells of muscle growth and regeneration—are affected.
Externí odkaz:
https://doaj.org/article/6e98c057ed4b4500b5bfe008d1e51f41
Autor:
Alessio Mancini, Filmon Eyassu, Maxwell Conway, Annalisa Occhipinti, Pietro Liò, Claudio Angione, Sandra Pucciarelli
Publikováno v:
BMC Bioinformatics, Vol 19, Iss S15, Pp 123-130 (2018)
Abstract Background The study of cell metabolism is becoming central in several fields such as biotechnology, evolution/adaptation and human disease investigations. Here we present CiliateGEM, the first metabolic network reconstruction draft of the f
Externí odkaz:
https://doaj.org/article/da6bd89a5e6649f49a5a02563c0fca9b
Publikováno v:
Mathematics, Vol 9, Iss 24, p 3262 (2021)
Identifying relevant genomic features that can act as prognostic markers for building predictive survival models is one of the central themes in medical research, affecting the future of personalized medicine and omics technologies. However, the high
Externí odkaz:
https://doaj.org/article/36662579cf9e4cebb08a0b72f97d4b21
Autor:
Annalisa Occhipinti, Filmon Eyassu, Thahira J. Rahman, Pattanathu K. S. M. Rahman, Claudio Angione
Publikováno v:
PeerJ, Vol 6, p e6046 (2018)
Background Rhamnolipids, biosurfactants with a wide range of biomedical applications, are amphiphilic molecules produced on the surfaces of or excreted extracellularly by bacteria including Pseudomonas aeruginosa. However, Pseudomonas putida is a non
Externí odkaz:
https://doaj.org/article/1944531da8404e26bdad0bd6e7af24a6
Combining Pathway Identification and Breast Cancer Survival Prediction via Screening-Network Methods
Publikováno v:
Frontiers in Genetics, Vol 9 (2018)
Breast cancer is one of the most common invasive tumors causing high mortality among women. It is characterized by high heterogeneity regarding its biological and clinical characteristics. Several high-throughput assays have been used to collect geno
Externí odkaz:
https://doaj.org/article/b4c09cfef94a45a09a87d6e80eeab786
Modelling circulating tumour cells for personalised survival prediction in metastatic breast cancer.
Publikováno v:
PLoS Computational Biology, Vol 11, Iss 5, p e1004199 (2015)
Ductal carcinoma is one of the most common cancers among women, and the main cause of death is the formation of metastases. The development of metastases is caused by cancer cells that migrate from the primary tumour site (the mammary duct) through t
Externí odkaz:
https://doaj.org/article/ac041d79a84b439788ea30d370c11532
Publikováno v:
Methods in molecular biology (Clifton, N.J.). 2553
Breast cancer is one of the most common cancers in women worldwide, which causes an enormous number of deaths annually. However, early diagnosis of breast cancer can improve survival outcomes enabling simpler and more cost-effective treatments. The r
Autor:
Maxime RF Gosselin, Virginie Mournetas, Malgorzata Borczyk, Suraj Verma, Annalisa Occhipinti, Justyna Róg, Lukasz Bozycki, Michal Korostynski, Samuel C Robson, Claudio Angione, Christian Pinset, Dariusz C Gorecki
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fd8e137fdb90207a89e7c8f06914349e
https://doi.org/10.7554/elife.75521.sa2
https://doi.org/10.7554/elife.75521.sa2