AIMC Topic: DNA

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SCP4ssd: A Serverless Platform for Nucleotide Sequence Synthesis Difficulty Prediction Using an AutoML Model.

Genes
DNA synthesis is widely used in synthetic biology to construct and assemble sequences ranging from short RBS to ultra-long synthetic genomes. Many sequence features, such as the GC content and repeat sequences, are known to affect the synthesis diffi...

A Grid Search-Based Multilayer Dynamic Ensemble System to Identify DNA N4-Methylcytosine Using Deep Learning Approach.

Genes
DNA (Deoxyribonucleic Acid) N4-methylcytosine (4mC), a kind of epigenetic modification of DNA, is important for modifying gene functions, such as protein interactions, conformation, and stability in DNA, as well as for the control of gene expression ...

Nucleic Acid Quantification by Multi-Frequency Impedance Cytometry and Machine Learning.

Biosensors
Determining nucleic acid concentrations in a sample is an important step prior to proceeding with downstream analysis in molecular diagnostics. Given the need for testing DNA amounts and its purity in many samples, including in samples with very smal...

Deep reinforcement learning-based pairwise DNA sequence alignment method compatible with embedded edge devices.

Scientific reports
Sequence alignment is an essential component of bioinformatics, for identifying regions of similarity that may indicate functional, structural, or evolutionary relationships between the sequences. Genome-based diagnostics relying on DNA sequencing ha...

SENIES: DNA Shape Enhanced Two-Layer Deep Learning Predictor for the Identification of Enhancers and Their Strength.

IEEE/ACM transactions on computational biology and bioinformatics
Identifying enhancers is a critical task in bioinformatics due to their primary role in regulating gene expression. For this reason, various computational algorithms devoted to enhancer identification have been put forward over the years. More featur...

iDRBP-EL: Identifying DNA- and RNA- Binding Proteins Based on Hierarchical Ensemble Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Identification of DNA-binding proteins (DBPs) and RNA-binding proteins (RBPs) from the primary sequences is essential for further exploring protein-nucleic acid interactions. Previous studies have shown that machine-learning-based methods can efficie...

Laplacian Regularized Sparse Representation Based Classifier for Identifying DNA N4-Methylcytosine Sites via L-Matrix Norm.

IEEE/ACM transactions on computational biology and bioinformatics
N4-methylcytosine (4mC) is one of important epigenetic modifications in DNA sequences. Detecting 4mC sites is time-consuming. The computational method based on machine learning has provided effective help for identifying 4mC. To further improve the p...

I-DNAN6mA: Accurate Identification of DNA N-Methyladenine Sites Using the Base-Pairing Map and Deep Learning.

Journal of chemical information and modeling
The recent discovery of numerous DNA N-methyladenine (6mA) sites has transformed our perception about the roles of 6mA in living organisms. However, our ability to understand them is hampered by our inability to identify 6mA sites rapidly and cost-ef...

Molecular Computation for Molecular Classification.

Advanced biology
DNA as an informational polymer has, for the past 30 years, progressively become an essential molecule to rationally build chemical reaction networks endowed with powerful signal-processing capabilities. Whether influenced by the silicon world or ins...

A universal deep-learning model for zinc finger design enables transcription factor reprogramming.

Nature biotechnology
CysHis zinc finger (ZF) domains engineered to bind specific target sequences in the genome provide an effective strategy for programmable regulation of gene expression, with many potential therapeutic applications. However, the structurally intricate...