0000000000208803

AUTHOR

Lukas Schmidt

showing 2 related works from this author

Machine learning of reverse transcription signatures of variegated polymerases allows mapping and discrimination of methylated purines in limited tra…

2020

AbstractReverse transcription (RT) of RNA templates containing RNA modifications leads to synthesis of cDNA containing information on the modification in the form of misincorporation, arrest, or nucleotide skipping events. A compilation of such events from multiple cDNAs represents an RT-signature that is typical for a given modification, but, as we show here, depends also on the reverse transcriptase enzyme. A comparison of 13 different enzymes revealed a range of RT-signatures, with individual enzymes exhibiting average arrest rates between 20 and 75%, as well as average misincorporation rates between 30 and 75% in the read-through cDNA. Using RT-signatures from individual enzymes to trai…

AdenosineAcademicSubjects/SCI00010Machine learningcomputer.software_genre[SDV.BBM.BM] Life Sciences [q-bio]/Biochemistry Molecular Biology/Molecular biologyMethylationMachine Learning03 medical and health sciences0302 clinical medicineComplementary DNA[SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry Molecular Biology/Genomics [q-bio.GN]GeneticsMolecular BiologyPolymerase030304 developmental biologychemistry.chemical_classification0303 health sciencesOligoribonucleotidesGuanosinebiologybusiness.industryRNA-Directed DNA PolymeraseRNARNA-Directed DNA Polymerase[SDV.BBM.BM]Life Sciences [q-bio]/Biochemistry Molecular Biology/Molecular biologyReverse TranscriptionMethylationReverse transcriptaseEnzymechemistryTransfer RNAbiology.protein[SDV.BBM.GTP] Life Sciences [q-bio]/Biochemistry Molecular Biology/Genomics [q-bio.GN]Artificial intelligenceTranscriptomebusinesscomputer030217 neurology & neurosurgery
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Graphical Workflow System for Modification Calling by Machine Learning of Reverse Transcription Signatures

2019

Modification mapping from cDNA data has become a tremendously important approach in epitranscriptomics. So-called reverse transcription signatures in cDNA contain information on the position and nature of their causative RNA modifications. Data mining of, e.g. Illumina-based high-throughput sequencing data, is therefore fast growing in importance, and the field is still lacking effective tools. Here we present a versatile user-friendly graphical workflow system for modification calling based on machine learning. The workflow commences with a principal module for trimming, mapping, and postprocessing. The latter includes a quantification of mismatch and arrest rates with single-nucleotide re…

0301 basic medicinelcsh:QH426-470Downstream (software development)Computer scienceRT signatureMachine learningcomputer.software_genre[SDV.BBM.BM] Life Sciences [q-bio]/Biochemistry Molecular Biology/Molecular biologyField (computer science)m1A03 medical and health sciencesRNA modifications0302 clinical medicineEpitranscriptomics[SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry Molecular Biology/Genomics [q-bio.GN]GeneticsTechnology and CodeGalaxy platformGenetics (clinical)ComputingMilieux_MISCELLANEOUSbusiness.industryPrincipal (computer security)[SDV.BBM.BM]Life Sciences [q-bio]/Biochemistry Molecular Biology/Molecular biologyAutomationWatson–Crick faceVisualizationlcsh:Geneticsmachine learningComputingMethodologies_PATTERNRECOGNITION030104 developmental biologyWorkflow030220 oncology & carcinogenesisMolecular Medicine[SDV.BBM.GTP] Life Sciences [q-bio]/Biochemistry Molecular Biology/Genomics [q-bio.GN]TrimmingArtificial intelligencebusinesscomputer
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