Author

Saleem Al Dajani

Brigham and Women's HospitalORCID 0000-0003-4116-6616Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Biophysics· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Abel Sanchez· 1 shared David FurmaniD· 1 shared Frédéric LaquaiiD· 1 shared John R. WilliamsiD· 1 shared Matías FuentealbaiD· 1 shared Michael P. SnyderiD· 1 shared Ting ZhaiiD· 1 shared Vadim N. GladysheviD· 1 shared

Activity by Year

2024-2026 · peak 2/yr

Co-Author Collaboration Network

8 top collaborators · 11 mutual co-author links

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1 shared paperBioinformatics

Abel Sanchez

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3 papers

Recent·Most cited

BioinformaticsMachine Learning HealthPeer-reviewedJul 2, 2026

DeepSeq: High-Throughput Single-Cell RNA Sequencing Data Labeling via Web Search-Augmented Agentic Generative AI Foundation Models

Saleem Al Dajani, Abel Sanchez, John R. Williams

This paper introduces DeepSeq, a method using agentic generative AI with web search to automate labeling of single-cell RNA sequencing data, achieving 82.5% accuracy.

2 citations

scRNA-seqdeep learning

𝕏 PostBluesky

Systems BiologybioRxivPreprintApr 8, 2026

Quantification of domain-specific intrinsic capacity using mortality data

Matías Fuentealba, Ting Zhai, Saleem Al Dajani…·David Furman

This study uses UK Biobank data to develop an 18-year mortality risk estimator for domain-specific intrinsic capacity, identifying immune system activation across domains.

DOI 10.64898/2026.04.06.714260

humanproteomics

𝕏 PostBluesky

BiophysicsbioRxivPreprintJul 15, 2024

Machine learning nominal max oxygen consumption from wearable reflective pulse oximetry with density functional theory

S. A. F. Al Dajani, Frédéric Laquai

The paper uses machine learning to infer maximum oxygen consumption from wearable pulse oximetry data, achieving high correlation with standard measurements.

DOI 10.1101/2024.07.15.603651

humanbulk RNA-seq

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