Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

GRIMM-II: A two-stage real-time algorithm for nine-locus HLA imputation and matching with up to three mismatches.

Human immunology - 1 Oct 2026

Kirshenboim Ofek, Kabya Amit, Yehezkel-Imra Regev, Tshuva Yuli, Maiers Martin, Gragert Loren, Bashyal Pradeep, Israeli Sapir, Louzoun Yoram

Abstract excerpt

BACKGROUND: The success of hematopoietic stem cell transplantation (HSCT) depends critically on human leukocyte antigen (HLA) matching between donor and recipient. While traditional matching focuses on five classical HLA loci (A, B, C, DRB1, DQB1), clinical practice increasingly considers extended typing at nine loci, including DPA1, DQA1, DPB1, and DRB3/4/5. Furthermore, emerging evidence supports...

Read the complete abstract on PubMed

Topics

Humans
Algorithms
Histocompatibility Testing
HLA Antigens
Hematopoietic Stem Cell Transplantation
Genotype

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Histocompatibility

Software

Alleles

Tissue Donors

Source

Open in PubMed Open full text

Identifiers

PMID: 42571736
DOI: 10.1016/j.humimm.2026.111810
PMCID: PMC13504538

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 25 Oct 2026.

Related research

Semantic proximity does not establish scientific evidence. Graph snapshot: 2026-09-29.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

GRIMM-II: A two-stage real-time algorithm for nine-locus HLA imputation and matching with up to three mismatches.PMID 42571736Read ↗

GRIMM-II: A Two-Stage Real-Time Algorithm for Nine-Locus HLA Imputation and Matching with Up to Three MismatchesSemantic proximity Read ↗

GRIMM: GRaph IMputation and matching for HLA genotypesSemantic proximity Read ↗

Combined imputation of HLA genotype and self-identified race leads to better donor-recipient matching.Semantic proximity Read ↗

Graph-Based Imputation Methods and Their Applications to Single Donors and Families.Semantic proximity Read ↗

Predicting HLA-DPB1 permissive probabilities through a DPB1 prediction service towards the optimization of HCT donor selection.Semantic proximity Read ↗

High-resolution HLA genotyping improves PIRCHE-II assessment of molecular mismatching in kidney transplantation.Semantic proximity Read ↗

A Tool for the Assessment of HLA-DQ Heterodimer Variation in Hematopoietic Cell Transplantation.Semantic proximity Read ↗

Landscapes of HLA Mismatching in Contemporary Unrelated Haematopoietic Cell Transplantation.Semantic proximity Read ↗

HapLogic: A Predictive Human Leukocyte Antigen–Matching Algorithm to Enhance Rapid Identification of the Optimal Unrelated Hematopoietic Stem Cell Sources for TransplantationSemantic proximity Read ↗

HLA haplotype frequency estimation for heterogeneous populations using a graph-based imputation algorithm.Semantic proximity Read ↗

Six-locus high resolution HLA haplotype frequencies derived from mixed-resolution DNA typing for the entire US donor registry.Semantic proximity Read ↗

The digital keystone: how artificial intelligence is reshaping HLA research and clinical practice.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.