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Oligonucleotides

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repDNA: a Python package to generate various modes of feature vectors for DNA sequences by incorporating user-defined physicochemical properties and sequence-order effects.

Bioinformatics (Oxford, England)
UNLABELLED: In order to develop powerful computational predictors for identifying the biological features or attributes of DNAs, one of the most challenging problems is to find a suitable approach to effectively represent the DNA sequences. To facili...

Structure-aware machine learning identifies microRNAs operating as Toll-like receptor 7/8 ligands.

RNA biology
MicroRNAs (miRNAs) can serve as activation signals for membrane receptors, a recently discovered function that is independent of the miRNAs' conventional role in post-transcriptional gene regulation. Here, we introduce a machine learning approach, Br...

Haruspex: A Neural Network for the Automatic Identification of Oligonucleotides and Protein Secondary Structure in Cryo-Electron Microscopy Maps.

Angewandte Chemie (International ed. in English)
In recent years, three-dimensional density maps reconstructed from single particle images obtained by electron cryo-microscopy (cryo-EM) have reached unprecedented resolution. However, map interpretation can be challenging, in particular if the const...

Mb-level CpG and TFBS islands visualized by AI and their roles in the nuclear organization of the human genome.

Genes & genetic systems
Unsupervised machine learning that can discover novel knowledge from big sequence data without prior knowledge or particular models is highly desirable for current genome study. We previously established a batch-learning self-organizing map (BLSOM) f...

Athena: Automated Tuning of k-mer based Genomic Error Correction Algorithms using Language Models.

Scientific reports
The performance of most error-correction (EC) algorithms that operate on genomics reads is dependent on the proper choice of its configuration parameters, such as the value of k in k-mer based techniques. In this work, we target the problem of findin...

Exploration of the nanomedicine-design space with high-throughput screening and machine learning.

Nature biomedical engineering
Only a tiny fraction of the nanomedicine-design space has been explored, owing to the structural complexity of nanomedicines and the lack of relevant high-throughput synthesis and analysis methods. Here, we report a methodology for determining struct...