Titlebook: HLA Typing; Methods and Protocol Sebastian Boegel Book 2024Latest edition The Editor(s) (if applicable) and The Author(s), under exclusive

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書目名稱HLA Typing影響因子(影響力)




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書目名稱HLA Typing網(wǎng)絡(luò)公開度學(xué)科排名




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書目名稱HLA Typing被引頻次學(xué)科排名




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書目名稱HLA Typing讀者反饋學(xué)科排名

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Allele Frequency Net Database, their corresponding alleles in worldwide human populations. At present, the website contains data from 1784 population samples in more than 14 million individuals from 129 countries on the frequency of genes from different polymorphic regions including data for the human leukocyte antigen (HLA) sys

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AmpliSAS and AmpliHLA: Web Server and Local Tools for MHC Typing of Non-model Species and Human Usize amplicon sequencing data from non-model species and it is able to perform de novo genotyping without any previous knowledge of the reference alleles. AmpliHLA is a human specific version; it performs HLA typing by comparing sequenced variants against human reference alleles from the IMGT/HLA data

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Comprehensive HLA Typing from a Current Allele Database Using Next-Generation Sequencing Data,d inflammation-related disorders, and donor selection in organ transplantation and regenerative medicine. To obtain this information, an accurate . typing method that is applicable for any allele registered in . allele databases is needed. Here we describe a method—called HLA-HD—for determining alle

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Deep Learning-Based HLA Allele Imputation Applicable to GWAS,genes are identified, to fully understand the genetic basis of human traits. Different HLA imputation methods have been developed, each with its own advantages, and recent methods have been improved in terms of imputation accuracy and computational costs. Here, I describe Deep*HLA, a recently publis

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Imputation-Based HLA Typing with GWAS SNPs, complex (MHC) region. These methods predict HLA classical alleles using dense SNP genotypes, commonly found on array-based platforms used in genome-wide association studies (GWAS). The analysis of HLA classical alleles can be conducted on current SNP datasets at no additional cost. Here, we describ

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