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Synthesis Success Calculator: Predicting the Rapid Synthesis of DNA Fragments with Machine Learning.

ACS synthetic biology
The synthesis and assembly of long DNA fragments has greatly accelerated synthetic biology and biotechnology research. However, long turnaround times or synthesis failures create unpredictable bottlenecks in the design-build-test-learn cycle. We deve...

Denoising DNA Encoded Library Screens with Sparse Learning.

ACS combinatorial science
DNA-encoded libraries (DELs) are large, pooled collections of compounds in which every library member is attached to a stretch of DNA encoding its complete synthetic history. DEL-based hit discovery involves affinity selection of the library against ...

A Generative Neural Network for Maximizing Fitness and Diversity of Synthetic DNA and Protein Sequences.

Cell systems
Engineering gene and protein sequences with defined functional properties is a major goal of synthetic biology. Deep neural network models, together with gradient ascent-style optimization, show promise for sequence design. The generated sequences ca...

Hereditary disease prediction in eukaryotic DNA: an adaptive signal processing approach.

Nucleosides, nucleotides & nucleic acids
Hereditary disease prediction in eukaryotic DNA using signal processing approaches is an incredible work in bioinformatics. Researchers of various fields are trying to put forth a noninvasive approach to forecast the disease-related genes. As disease...

Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis.

Journal of visualized experiments : JoVE
Glomerular cell death is a pathological feature of myeloperoxidase anti neutrophil cytoplasmic antibody associated vasculitis (MPO-AAV). Extracellular deoxyribonucleic acid (ecDNA) is released during different forms of cell death including apoptosis,...

Machine Learning on DNA-Encoded Libraries: A New Paradigm for Hit Finding.

Journal of medicinal chemistry
DNA-encoded small molecule libraries (DELs) have enabled discovery of novel inhibitors for many distinct protein targets of therapeutic value. We demonstrate a new approach applying machine learning to DEL selection data by identifying active molecul...

Decoding whole-genome mutational signatures in 37 human pan-cancers by denoising sparse autoencoder neural network.

Oncogene
Millions of somatic mutations have recently been discovered in cancer genomes. These mutations in cancer genomes occur due to internal and external mutagenesis forces. Decoding the mutational processes by examining their unique patterns has successfu...

Homogeneous DNA-only keypad locks enable one-pot assay of multi-inputs.

Chemical communications (Cambridge, England)
Homogeneous DNA-only keypad locks were built with multi-stranded scalable junction substrates and a series of double-stranded eliminators to differentially process correctly- and wrongly-added DNA inputs, respectively. Unlike conventional strategies ...

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...

Multiview learning for understanding functional multiomics.

PLoS computational biology
The molecular mechanisms and functions in complex biological systems currently remain elusive. Recent high-throughput techniques, such as next-generation sequencing, have generated a wide variety of multiomics datasets that enable the identification ...