QuickProbs 2: towards rapid construction of high-quality alignments of large protein families
원문 초록
Increasing size of sequence databases caused by the development of high throughput sequencing, poses multiple alignment algorithms to face one of the greatest challenges yet. As we show, well-established techniques employed for increasing alignment quality, i.e., refinement and consistency, are ineffective when large protein families are of interest. We present QuickProbs 2, an algorithm for multiple sequence alignment. Based on probabilistic models, equipped with novel column-oriented refinement and selective consistency, it offers outstanding accuracy. When analysing hundreds of sequences, QuickProbs 2 is significantly better than Clustal Omega, the previous leader for processing numerous protein families. In the case of smaller sets, for which consistency-based methods are the best performing, QuickProbs 2 is also superior to the competitors. Due to computational scalability of selective consistency and utilisation of massively parallel architectures, presented algorithm is comparable to Clustal Omega in terms of execution time, and orders of magnitude faster than full consistency approaches, like MSAProbs or PicXAA. All these make QuickProbs 2 a useful tool for aligning families ranging from few, to hundreds of proteins. QuickProbs 2 is available at https://github.com/refresh-bio/QuickProbs.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
MSAGPT: Neural Prompting Protein Structure Prediction via MSA Generative Pre-Training
ESM-NBR: fast and accurate nucleic acid-binding residue prediction via protein language model feature representation and multi-task learning
PEvoLM: Protein Sequence Evolutionary Information Language Model
PoET: A generative model of protein families as sequences-of-sequences
Enhancing the Protein Tertiary Structure Prediction by Multiple Sequence Alignment Generation
ApHMM: Accelerating Profile Hidden Markov Models for Fast and Energy-Efficient Genome Analysis
토론
이 논문과 연결된 포럼 글이 아직 없습니다.