A New Framework For Spatial Modeling And Synthesis of Genome Sequence
This paper provides a framework in order to statistically model sequences from human genome, which is allowing a formulation to synthesize gene sequences. We start by converting the alphabetic sequence of genome to decimal sequence by Huffman coding. Then, this decimal sequence is decomposed by HP filter into two components, trend and cyclic. Next, a statistical modeling, ARIMA-GARCH, is implemented on trend component exhibiting heteroskedasticity, autoregressive integrated moving average (ARIMA) to capture the linear characteristics of the sequence and later, generalized autoregressive conditional heteroskedasticity (GARCH) is then appropriated for the statistical nonlinearity of genome sequence. This modeling approach synthesizes a given genome sequence regarding to its statistical features. Finally, the PDF of a given sequence is estimated using Gaussian mixture model and based on estimated PDF, we determine a new PDF presenting sequences that counteract statistically the original sequence. Our strategy is performed on several genes as well as HIV nucleotide sequence and corresponding results is presented.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
A generative nonparametric Bayesian model for whole genomes
Generative probabilistic modeling of biological sequences has widespread existing and potential use across biology and biomedicine, particularly given advances in high-throughput sequencing, synthesis and editing. Howeve…
Density Estimationmodelparameter estimationA generative nonparametric Bayesian model for whole genomes
Generative probabilistic modeling of biological sequences has widespread existing and potential use across biology and biomedicine, particularly given advances in high-throughput sequencing, synthesis and editing. Howeve…
Density Estimationparameter estimationUNADON: Transformer-based model to predict genome-wide chromosome spatial position
The spatial positioning of chromosomes relative to functional nuclear bodies is intertwined with genome functions such as transcription. However, the sequence patterns and epigenomic features that collectively influence …
PositionRandom Fragments Classification of Microbial Marker Clades with Multi-class SVM and N-Best Algorithm
Microbial clades modeling is a challenging problem in biology based on microarray genome sequences, especially in new species gene isolates discovery and category. Marker family genome sequences play important roles in d…
General ClassificationTime SeriesTime Series AnalysisA Probabilistic Framework for Imputing Genetic Distances in Spatiotemporal Pathogen Models
Pathogen genome data offers valuable structure for spatial models, but its utility is limited by incomplete sequencing coverage. We propose a probabilistic framework for inferring genetic distances between unsequenced ca…
Imputation