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| http://dx.doi.org/10.1007/s00063-024-01146-8 | DOI Listing |
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Comparative analysis of regression algorithms for drug response prediction using GDSC dataset.
BMC Res Notes
January 2025
Department of Computer Engineering, Chungbuk National University, Chungdae-ro 1, Cheongju, 28644, Republic of Korea.
Background: Drug response prediction can infer the relationship between an individual's genetic profile and a drug, which can be used to determine the choice of treatment for an individual patient. Prediction of drug response is recently being performed using machine learning technology. However, high-throughput sequencing data produces thousands of features per patient.
View Article and Find Full Text PDFThe microenvironment cell index is a novel indicator for the prognosis and therapeutic regimen selection of cancers.
J Transl Med
January 2025
Department of Stem Cell and Regenerative Medicine, Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, 400038, China.
Background: It is worthwhile to establish a prognostic prediction model based on microenvironment cells (MCs) infiltration and explore new treatment strategies for triple-negative breast cancer (TNBC).
Methods: The xCell algorithm was used to quantify the cellular components of the TNBC microenvironment based on bulk RNA sequencing (bulk RNA-seq) data. The MCs index (MCI) was constructed using the least absolute shrinkage and selection operator Cox (LASSO-Cox) regression analysis.
Fragmenstein: predicting protein-ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding-based methodology.
J Cheminform
January 2025
Oxford Protein Informatics Group, Department of Statistics, University of Oxford, Oxford, UK.
Current strategies centred on either merging or linking initial hits from fragment-based drug design (FBDD) crystallographic screens generally do not fully leaverage 3D structural information. We show that an algorithmic approach (Fragmenstein) that 'stitches' the ligand atoms from this structural information together can provide more accurate and reliable predictions for protein-ligand complex conformation than general methods such as pharmacophore-constrained docking. This approach works under the assumption of conserved binding: when a larger molecule is designed containing the initial fragment hit, the common substructure between the two will adopt the same binding mode.
View Article and Find Full Text PDFEstablishment and validation of predictive model of ARDS in critically ill patients.
J Transl Med
January 2025
Department of Critical Care Medicine, Peking University Third Hospital, Beijing, 100191, China.
Background: Acute respiratory distress syndrome (ARDS) is a prevalent complication among critically ill patients, constituting around 10% of intensive care unit (ICU) admissions and mortality rates ranging from 35 to 46%. Hence, early recognition and prediction of ARDS are crucial for the timely administration of targeted treatment. However, ARDS is frequently underdiagnosed or delayed, and its heterogeneity diminishes the clinical utility of ARDS biomarkers.
View Article and Find Full Text PDFIdentification of key genes associated with oxidative stress in ischemic stroke via bioinformatics integrated analysis.
BMC Neurosci
January 2025
Department of General Practice, Shanghai Xuhui Central Hospital, Shanghai, China.
Background: Ischemic stroke (IS) is a common cerebrovascular disease. Although the formation of atherosclerosis, which is closely related to oxidative stress (OS), is associated with stroke-related deaths. However, the role of OS in IS is unknown.
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