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A Multi-Objective Approach for Anti-Osteosarcoma Cancer Agents Discovery through Drug Repurposing
(MDPI AG, 2020-11-22)
[Abstract]
Osteosarcoma is the most common type of primary malignant bone tumor. Although nowadays 5-year survival rates can reach up to 60–70%, acute complications and late effects of osteosarcoma therapy are two of the ...
Net-Net AutoML Selection of Artificial Neural Network Topology for Brain Connectome Prediction
(MDPI, 2020-02-14)
[Abstract]
Brain Connectome Networks (BCNs) are defined by brain cortex regions (nodes) interacting with others by electrophysiological co-activation (edges). The experimental prediction of new interactions in BCNs ...
Automatic Assessment of Alzheimer’s Disease Diagnosis Based on Deep Learning Techniques
(Elsevier, 2020-05)
[Abstract]
Early detection is crucial to prevent the progression of Alzheimer’s disease (AD). Thus, specialists can begin preventive treatment as soon as possible. They demand fast and precise assessment in the diagnosis ...
Gene Prioritization through Consensus Strategy, Enrichment Methodologies Analysis, and Networking for Osteosarcoma Pathogenesis
(M D P I AG, 2020-02-05)
[Abstract] Osteosarcoma is the most common subtype of primary bone cancer, affecting mostly adolescents. In recent years, several studies have focused on elucidating the molecular mechanisms of this sarcoma; however, its ...
OncoOmics approaches to reveal essential genes in breast cancer: a panoramic view from pathogenesis to precision medicine
(Springer Nature, 2020-03-24)
[Abstract]
Breast cancer (BC) is the leading cause of cancer-related death among women and the most commonly diagnosed cancer worldwide. Although in recent years large-scale efforts have focused on identifying new therapeutic ...
Perturbation-Theory Machine Learning (PTML) Multilabel Model of the ChEMBL Dataset of Preclinical Assays for Antisarcoma Compounds
(American Chemical Society, 2020-10-14)
[Abstract]
Sarcomas are a group of malignant neoplasms of connective tissue with a different etiology than carcinomas. The efforts to discover new drugs with antisarcoma activity have generated large datasets of multiple ...
Applying Artificial Intelligence for Operating System Fingerprinting
(MDPI, 2021)
[Abstract] In the field of computer security, the possibility of knowing which specific version of an operating system is running behind a machine can be useful, to assist in a penetration test or monitor the devices ...
Prediction of Breast Cancer Proteins Involved in Immunotherapy, Metastasis, and RNA-Binding Using Molecular Descriptors and Artifcial Neural Networks
(Springer Nature, 2020-05-22)
[Abstract]
Breast cancer (BC) is a heterogeneous disease where genomic alterations, protein expression
deregulation, signaling pathway alterations, hormone disruption, ethnicity and environmental
determinants are involved. ...
Molecular Docking and Machine Learning Analysis of Abemaciclib in Colon Cancer
(BioMed Central Ltd., 2020-07-08)
[Abstract]
Background -
The main challenge in cancer research is the identification of different omic variables that present a prognostic value and personalised diagnosis for each tumour. The fact that the diagnosis is ...