Alsaafin Areej, Tizhoosh Hamid R
Department of Artificial Intelligence & Informatics, KIMIA Lab, Mayo Clinic, Rochester, MN, 55905, United States.
Biol Methods Protoc. 2024 Jul 30;9(1):bpae055. doi: 10.1093/biomethods/bpae055. eCollection 2024.
We present SEQuence Weighted Alignment for Sorting and Harmonization (Seqwash), an algorithm designed to process sequencing profiles utilizing large language models. Seqwash immune cell sequences into a unified representation, empowering LLMs to embed meaningful patterns while eliminating irrelevant information. Evaluations using immune cell sequencing data showcase Seqwash's efficacy in standardizing profiles, leading to improved feature quality and enhanced performance in both supervised and unsupervised downstream tasks for sequencing data.
我们提出了用于排序和协调的序列加权比对(Seqwash),这是一种利用大语言模型来处理测序图谱的算法。Seqwash将免疫细胞序列转化为统一的表示形式,使大语言模型能够嵌入有意义的模式,同时消除无关信息。使用免疫细胞测序数据进行的评估表明,Seqwash在标准化图谱方面具有有效性,从而在测序数据的监督和无监督下游任务中提高了特征质量并增强了性能。