scholarly journals Raman Molecular Fingerprints of SARS‐CoV‐2 British Variant and the Concept of Raman Barcode

2021 ◽  
pp. 2103287
Author(s):  
Giuseppe Pezzotti ◽  
Francesco Boschetto ◽  
Eriko Ohgitani ◽  
Yuki Fujita ◽  
Masaharu Shin‐Ya ◽  
...  
Keyword(s):  
Molecular Fingerprints

Molecular fingerprints based on Jacobi expansions of electron densities

2021 ◽  
Vol 140 (2) ◽  
Author(s):  
Rafael López ◽  
Frank Martínez ◽  
José Manuel García de la Vega
Keyword(s):  
Electron Densities ◽  
Molecular Fingerprints ◽  
Jacobi Expansions

scholarly journals Random forest classification for predicting lifespan-extending chemical compounds

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sofia Kapsiani ◽  
Brendan J. Howlin
Keyword(s):  
Caenorhabditis Elegans ◽  
Random Forest ◽  
Molecular Descriptors ◽  
Area Under The Curve ◽  
Chemical Compounds ◽  
Research Area ◽  
Importance Measure ◽  
Random Forest Algorithm ◽  
Molecular Fingerprints ◽  
Age Related

AbstractAgeing is a major risk factor for many conditions including cancer, cardiovascular and neurodegenerative diseases. Pharmaceutical interventions that slow down ageing and delay the onset of age-related diseases are a growing research area. The aim of this study was to build a machine learning model based on the data of the DrugAge database to predict whether a chemical compound will extend the lifespan of Caenorhabditis elegans. Five predictive models were built using the random forest algorithm with molecular fingerprints and/or molecular descriptors as features. The best performing classifier, built using molecular descriptors, achieved an area under the curve score (AUC) of 0.815 for classifying the compounds in the test set. The features of the model were ranked using the Gini importance measure of the random forest algorithm. The top 30 features included descriptors related to atom and bond counts, topological and partial charge properties. The model was applied to predict the class of compounds in an external database, consisting of 1738 small-molecules. The chemical compounds of the screening database with a predictive probability of ≥ 0.80 for increasing the lifespan of Caenorhabditis elegans were broadly separated into (1) flavonoids, (2) fatty acids and conjugates, and (3) organooxygen compounds.

Prediction of hERG potassium channel blockage using ensemble learning methods and molecular fingerprints

2020 ◽  
Vol 332 ◽  
pp. 88-96 ◽  
Author(s):  
Miao Liu ◽  
Li Zhang ◽  
Shimeng Li ◽  
Tianzhou Yang ◽  
Lili Liu ◽  
...  
Keyword(s):  
Potassium Channel ◽  
Ensemble Learning ◽  
Learning Methods ◽  
Molecular Fingerprints ◽  
Channel Blockage

scholarly journals Spatial transcriptomics reveals unique molecular fingerprints of human nociceptors

2021 ◽  
Author(s):  
Diana Tavares-Ferreira ◽  
Stephanie Shiers ◽  
Pradipta R. Ray ◽  
Andi Wangzhou ◽  
Vivekanand Jeevakumar ◽  
...  
Keyword(s):  
Sex Differences ◽  
Sensory Neurons ◽  
Dorsal Root ◽  
Expression Profiles ◽  
Organ Donors ◽  
Drg Neurons ◽  
Pain Mechanisms ◽  
Molecular Fingerprints ◽  
Sensory Disorders

AbstractSingle-cell transcriptomics on mouse nociceptors has transformed our understanding of pain mechanisms. Equivalent information from human nociceptors is lacking. We used spatial transcriptomics to molecularly characterize transcriptomes of single dorsal root ganglion (DRG) neurons from 8 organ donors. We identified 10 clusters of human sensory neurons, 6 of which are C nociceptors, 1 Aβ nociceptor, 1 Aδ, and 2 Aβ subtypes. These neuron subtypes have distinct expression profiles from rodents and non-human primates and we identify new markers for each of these subtypes that can be applied broadly in human studies. We also identify sex differences, including a marked increase in CALCA expression in female putative itch nociceptors. Our data open the door to new pain targets and unparalleled molecular characterization of clinical sensory disorders.One Sentence SummaryThree A-fiber mechanoreceptor and seven nociceptor subtypes are identified, revealing sex differences and unique aspects of human DRG neurons.

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