AIMC Topic: DNA

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Reservoir Computing Using DNA Oscillators.

ACS synthetic biology Jan 26, 2022
This paper presents novel implementations for reservoir computing (RC) using DNA . An RC system consists of two parts: and . The reservoir projects input signals into a high-dimensional feature space which is formed by the of the reservoir. The int...
Neural Networks, Computer DNA
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NoAS-DS: Neural optimal architecture search for detection of diverse DNA signals.

Neural networks : the official journal of the International Neural Network Society Dec 23, 2021
Neural network architectures are high-performing variable models that can solve many learning tasks. Designing architectures manually require substantial time and also prior knowledge and expertise to develop a high-accuracy model. Most of the archit...
Generalization, Psychological Neural Networks, Computer DNA Data Collection Image Processing, Computer-Assisted
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Manipulation of Multiple Cell-Cell Interactions by Tunable DNA Scaffold Networks.

Angewandte Chemie (International ed. in English) Dec 23, 2021
Manipulation of cell-cell interactions via cell surface engineering has potential biomedical applications in tissue engineering and cell therapy. However, manipulation of the comprehensive and multiple intercellular interactions remains a challenge a...
Hep G2 Cells DNA Humans Neural Networks, Computer HeLa Cells Polymers Cell Communication
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NGS read classification using AI.

PloS one Dec 22, 2021
Clinical metagenomics is a powerful diagnostic tool, as it offers an open view into all DNA in a patient's sample. This allows the detection of pathogens that would slip through the cracks of classical specific assays. However, due to this unspecific...
Viruses Metagenome High-Throughput Nucleotide Sequencing Metagenomics Bacteria DNA, Bacterial Algorithms DNA, Viral Humans Animals DNA Neural Networks, Computer
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Deep transformers and convolutional neural network in identifying DNA N6-methyladenine sites in cross-species genomes.

Methods (San Diego, Calif.) Dec 13, 2021
As one of the most common post-transcriptional epigenetic modifications, N6-methyladenine (6 mA), plays an essential role in various cellular processes and disease pathogenesis. Therefore, accurately identifying 6 mA modifications is necessary for a ...
Neural Networks, Computer Software Genome Epigenesis, Genetic DNA
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CoRE-ATAC: A deep learning model for the functional classification of regulatory elements from single cell and bulk ATAC-seq data.

PLoS computational biology Dec 13, 2021
Cis-Regulatory elements (cis-REs) include promoters, enhancers, and insulators that regulate gene expression programs via binding of transcription factors. ATAC-seq technology effectively identifies active cis-REs in a given cell type (including from...
Humans Cells, Cultured DNA Regulatory Sequences, Nucleic Acid Chromatin Immunoprecipitation Sequencing Islets of Langerhans Computational Biology Monocytes Deep Learning Single-Cell Analysis
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BiLSTM-5mC: A Bidirectional Long Short-Term Memory-Based Approach for Predicting 5-Methylcytosine Sites in Genome-Wide DNA Promoters.

Molecules (Basel, Switzerland) Dec 7, 2021
An important reason of cancer proliferation is the change in DNA methylation patterns, characterized by the localized hypermethylation of the promoters of tumor-suppressor genes together with an overall decrease in the level of 5-methylcytosine (5mC)...
Promoter Regions, Genetic 5-Methylcytosine Neoplasms Deep Learning DNA Methylation DNA Neural Networks, Computer Aging Humans
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Predicting environmentally responsive transgenerational differential DNA methylated regions (epimutations) in the genome using a hybrid deep-machine learning approach.

BMC bioinformatics Nov 30, 2021
BACKGROUND: Deep learning is an active bioinformatics artificial intelligence field that is useful in solving many biological problems, including predicting altered epigenetics such as DNA methylation regions. Deep learning (DL) can learn an informat...
Genome, Human DNA Methylation DNA Epigenesis, Genetic Rats Machine Learning Humans Animals Artificial Intelligence
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Accelerating AFM Characterization via Deep-Learning-Based Image Super-Resolution.

Small (Weinheim an der Bergstrasse, Germany) Nov 27, 2021
Atomic force microscopy (AFM) is one of the most popular imaging and characterizing methods applicable to a wide range of nanoscale material systems. However, high-resolution imaging using AFM generally suffers from a low scanning yield due to its me...
Microscopy, Atomic Force Deep Learning DNA
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Explainable artificial intelligence in forensics: Realistic explanations for number of contributor predictions of DNA profiles.

Forensic science international. Genetics Nov 21, 2021
Machine learning obtains good accuracy in determining the number of contributors (NOC) in short tandem repeat (STR) mixture DNA profiles. However, the models used so far are not understandable to users as they only output a prediction without any rea...
Humans Artificial Intelligence Machine Learning DNA Forensic Medicine
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