C
Carlos Fernandez-Lozano
Researcher at University of A Coruña
Publications - 76
Citations - 769
Carlos Fernandez-Lozano is an academic researcher from University of A Coruña. The author has contributed to research in topics: Feature selection & Support vector machine. The author has an hindex of 15, co-authored 72 publications receiving 496 citations.
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A review on machine learning approaches and trends in drug discovery.
Paula Carracedo-Reboredo,Jose Liñares-Blanco,Nereida Rodriguez-Fernandez,Francisco Cedrón,Francisco J. Novoa,Adrian Carballal,Victor Maojo,Alejandro Pazos,Carlos Fernandez-Lozano +8 more
TL;DR: In this paper, a review of the state of the art in machine learning for drug discovery is presented, focusing mainly on the methods used to model the molecular data, as well as the biological problems addressed and the Machine Learning algorithms used for drugs discovery in recent years.
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RRegrs: an R package for computer-aided model selection with multiple regression models
Georgia Tsiliki,Cristian R. Munteanu,Cristian R. Munteanu,Jose A. Seoane,Carlos Fernandez-Lozano,Haralambos Sarimveis,Egon Willighagen +6 more
TL;DR: Good performance as well as its adaptability in terms of parameter optimization could make RRegrs a popular framework to assist the initial exploration of predictive models, and with that, the design of more comprehensive in silico screening applications.
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Classification of mild cognitive impairment and Alzheimer's Disease with machine-learning techniques using 1H Magnetic Resonance Spectroscopy data
Cristian R. Munteanu,Carlos Fernandez-Lozano,Virginia Mato Abad,Salvador Pita Fernández,Juan Álvarez-Linera,Juan Antonio Hernández-Tamames,Alejandro Pazos +6 more
TL;DR: It is suggested that knowing the composition of white and grey matter and cerebrospinal fluid of the spectroscopic voxel is essential in a 1H-MRS study to improve the accuracy of the quantifications and classifications, particularly in those studies involving elder patients and neurodegenerative diseases.
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Solvent Accessible Surface Area-Based Hot-Spot Detection Methods for Protein–Protein and Protein–Nucleic Acid Interfaces
Cristian R. Munteanu,António Pimenta,Carlos Fernandez-Lozano,André Melo,Maria Natalia Dias Soeiro Cordeiro,Irina S. Moreira,Irina S. Moreira +6 more
TL;DR: New models to predict HS for protein-protein and protein-nucleic acid interactions with better statistics compared with the ones currently reported in literature are presented.
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ISG15, a Small Molecule with Huge Implications: Regulation of Mitochondrial Homeostasis.
TL;DR: The essential functions of mitochondria in the antiviral response are discussed and the role of ISG15 in the regulation of mitochondrial processes, specifically OXPHOS and mitophagy is examined.