Beyond similarity assessment: Selecting the optimal model for sequence alignment via the Factorized Asymptotic Bayesian algorithm
Pair Hidden Markov Models (PHMMs) are probabilistic models used for pairwise sequence alignment, a quintessential problem in bioinformatics. PHMMs include three types of hidden states: match, insertion and deletion. Most previous studies have used one or two hidden states for each PHMM state type. However, few studies have examined the number of states suitable for representing sequence data or improving alignment accuracy.We developed a novel method to select superior models (including the number of hidden states) for PHMM. Our method selects models with the highest posterior probability using Factorized Information Criteria (FIC), which is widely utilised in model selection for probabilistic models with hidden variables. Our simulations indicated this method has excellent model selection capabilities with slightly improved alignment accuracy. We applied our method to DNA datasets from 5 and 28 species, ultimately selecting more complex models than those used in previous studies.
Code (0)
등록된 구현이 없습니다.
Tasks
Model SelectionSimilar Papers 제목 키워드 기반
CLAMS: A System for Zero-Shot Model Selection for Clustering
We propose an AutoML system that enables model selection on clustering problems by leveraging optimal transport-based dataset similarity. Our objective is to establish a comprehensive AutoML pipeline for clustering probl…
AutoMLClusteringModel SelectionLinear normalised hash function for clustering gene sequences and identifying reference sequences from multiple sequence alignments
The aim of this study was to develop a method that would identify the cluster centroids and the optimal number of clusters for a given sensitivity level and could work equally well for the different sequence datasets. A …
ClusteringDimensionality ReductionMultiple Sequence AlignmentSCAN: Self-and-Collaborative Attention Network for Video Person Re-identification
Video person re-identification attracts much attention in recent years. It aims to match image sequences of pedestrians from different camera views. Previous approaches usually improve this task from three aspects, inclu…
Person Re-IdentificationVideo-Based Person Re-IdentificationPairBench: A Systematic Framework for Selecting Reliable Judge VLMs
As large vision language models (VLMs) are increasingly used as automated evaluators, understanding their ability to effectively compare data pairs as instructed in the prompt becomes essential. To address this, we prese…
Protein model quality assessment using rotation-equivariant, hierarchical neural networks
Proteins are miniature machines whose function depends on their three-dimensional (3D) structure. Determining this structure computationally remains an unsolved grand challenge. A major bottleneck involves selecting the …