Bayesian inference of origin firing time distributions, origin interference and licencing probabilities from Next Generation Sequencing data

Sequence Fusion Algorithm of Tumor Gene Sequencing and Alignment Based on Machine Learning

With the rapid development of DNA high-throughput testing technology, there is a high correlation between DNA sequence variation and human diseases, and detecting whether there is variation in DNA sequence has become a hot research topic at present. DNA sequence variation is relatively rare, and the establishment of DNA sequence sparse matrix, which can quickly detect and reason fusion variation point, has become an important work of tumor gene testing. Because there are differences between the current comparison software and mutation detection software in detecting the same sample, there are errors between the results of derivative sequence comparison and the detection of mutation. In this paper, SNP and InDel detection methods based on machine learning and sparse matrix detection are proposed, and VarScan 2, Genome Analysis Toolkit (GATK), BCFtools, and FreeBayes are compared. In the research of SNP and InDel detection with intelligent reasoning, the experimental results show that the detection accuracy and recall rate are better when the depth is increasing. The reasoning fusion method proposed in this paper has certain advantages in comparison effect and discovery in SNP and InDel and has good effect on swelling and pain gene detection.

Metazoan DNA replication origins

DNA replication starts with the opening of DNA at sites called DNA replication origins. From the single sequence-specific DNA replication origin of the small Escherichia coli genome, up to thousands of origins that are necessary to replicate the large human genome, strict sequence specificity has been lost. Nevertheless, genome-wide analyses performed in the recent years, using different mapping methods, demonstrated that there are precise locations along the metazoan genome from which replication initiates. These sites contain relaxed sequence consensus and epigenetic features. There is flexibility in the choice of origins to be used during a given cell cycle, probably imposed by evolution and developmental constraints. Here, we will briefly describe their main features.