A5048352146- Machine Learning in Bioinformatics
- RNA and protein synthesis mechanisms
- Genomics and Phylogenetic Studies
- Fractal and DNA sequence analysis
- Evolution and Genetic Dynamics
- Genetics, Bioinformatics, and Biomedical Research
- Evolutionary Algorithms and Applications
- Chromosomal and Genetic Variations
- Protein Structure and Dynamics
- Genomics and Chromatin Dynamics
- CRISPR and Genetic Engineering
- SARS-CoV-2 and COVID-19 Research
- vaccines and immunoinformatics approaches
- Stability and Control of Uncertain Systems
- Bacteriophages and microbial interactions
- Chaos control and synchronization
- Genetic Mapping and Diversity in Plants and Animals
- Target Tracking and Data Fusion in Sensor Networks
Tsinghua University
2023-2024
Chromosomal fusion is a significant form of structural variation, but research into algorithms for its identification has been limited. Most existing methods rely on synteny analysis, which necessitates manual annotations and always involves inefficient sequence alignments. In this paper, we present novel alignment-free algorithm chromosomal recognition. Our method transforms the problem series assignment problems using natural vectors efficiently solves them with Kuhn-Munkres algorithm....
Understanding the structural similarity between genomes is pivotal in classification and phylogenetic analysis. As number of known rockets, alignment-free methods have gained considerable attention. Among these methods, natural vector method stands out as it represents sequences vectors using statistical moments, enabling effective clustering based on families biological taxonomy. However, determining an optimal metric that combines different elements remains challenging due to absence a...
Abstract Predicting the strength of promoters and guiding their directed evolution is a crucial task in synthetic biology. This approach significantly reduces experimental costs conventional promoter engineering. Previous studies employing machine learning or deep methods have shown some success this task, but outcomes were not satisfactory enough, primarily due to neglect evolutionary information. In paper, we introduce Chaos-Attention net for Promoter Evolution (CAPE) address limitations...
The highly variable SARS-CoV-2 virus responsible for the COVID-19 pandemic frequently undergoes mutations, leading to emergence of new variants that present novel threats public health. determination these often relies on manual definition based local sequence characteristics, resulting in delays their detection relative actual emergence. In this study, we propose an algorithm automatic identification variants. By leveraging optimal natural metric viruses alignment-free perspective measure...
Abstract Understanding the differences between genomic sequences of different lives is crucial for biological classification and phylogeny. Here, we downloaded all reliable seven kingdoms determined dimensions genome space embedded in Euclidean space, along with corresponding Natural Metrics. The concept Grand Biological Universe further proposed. In grand universe, convex hulls formed by universes are mutually disjoint, groups within each kingdom disjoint. This study provides a novel...
Ever since the Lie algebra method was introduced to construct finite dimensional nonlinear filters by Brockett and Mitter independently, there has been an intense interest in classifying all estimation algebras finding new classes of recursive filters. The proven be invaluable tool filtering theory. This paper considers derived from a system with state dimension <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math...
Abstract Predicting the strength of promoters and guiding their directed evolution is a crucial task in synthetic biology. This approach significantly reduces experimental costs conventional promoter engineering. Previous studies employing machine learning or deep methods have shown some success this task, but outcomes were not satisfactory enough, primarily due to neglect evolutionary information. In paper, we introduce Chaos-Attention net for Promoter Evolution (CAPE) address limitations...