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Uncovering blood-brain barrier permeability: a comparative study of machine learning models using molecular fingerprints, and SHAP explainability.
SAR QSAR Environ Res
December 2024
School of Computing and Data Sciences, FLAME University, Pune, India.
This study illustrates the use of chemical fingerprints with machine learning for blood-brain barrier (BBB) permeability prediction. Employing the Blood Brain Barrier Database (B3DB) dataset for BBB permeability prediction, we extracted nine different fingerprints. Support Vector Machine (SVM) and Extreme Gradient Boosting (XGBoost) algorithms were used to develop models for permeability prediction.
View Article and Find Full Text PDFSingle-Sample Networks Reveal Intra-Cytoband Co-Expression Hotspots in Breast Cancer Subtypes.
Int J Mol Sci
November 2024
Computational Genomics Division, National Institute of Genomic Medicine, Mexico City 14610, Mexico.
Breast cancer is a heterogeneous disease comprising various subtypes with distinct molecular characteristics, clinical outcomes, and therapeutic responses. This heterogeneity evidences significant challenges for diagnosis, prognosis, and treatment. Traditional genomic co-expression network analyses often overlook individual-specific interactions critical for personalized medicine.
View Article and Find Full Text PDFIntegrated single-cell analysis reveals distinct epigenetic-regulated cancer cell states and a heterogeneity-guided core signature in tamoxifen-resistant breast cancer.
Genome Med
November 2024
Data Science Institute, MCW Cancer Center and Mellowes Center for Genome Science and Precision Medicine, Medical College of Wisconsin, Milwaukee, WI, 53226, USA.
Background: Inter- and intra-tumor heterogeneity is considered a significant factor contributing to the development of endocrine resistance in breast cancer. Recent advances in single-cell RNA sequencing (scRNA-seq) and single-cell ATAC sequencing (scATAC-seq) allow us to explore inter- and intra-tumor heterogeneity at single-cell resolution. However, such integrated single-cell analysis has not yet been demonstrated to characterize the transcriptome and chromatin accessibility in breast cancer endocrine resistance.
View Article and Find Full Text PDFsimona: a comprehensive R package for semantic similarity analysis on bio-ontologies.
BMC Genomics
September 2024
Molecular Precision Oncology Program, National Center for Tumor Diseases (NCT), Im Neuenheimer Feld 280, Heidelberg, 69120, Germany.
Background: Bio-ontologies are keys in structuring complex biological information for effective data integration and knowledge representation. Semantic similarity analysis on bio-ontologies quantitatively assesses the degree of similarity between biological concepts based on the semantics encoded in ontologies. It plays an important role in structured and meaningful interpretations and integration of complex data from multiple biological domains.
View Article and Find Full Text PDFGenetically encoded fluorescent reporter for polyamines.
bioRxiv
November 2024
Whitehead Institute of Biomedical Research, Cambridge, MA, USA.
Polyamines are abundant and evolutionarily conserved metabolites that are essential for life. Dietary polyamine supplementation extends life-span and health-span. Dysregulation of polyamine homeostasis is linked to Parkinson's disease and cancer, driving interest in therapeutically targeting this pathway.
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