Atif Hasan Rahman

The paper introduces a reference-free scRNA-seq analysis method using k-mers, identifies elevated rRNA and mtRNA transcription during axolotl neurogenesis, and detects other RNA features in disease datasets.

This paper introduces an alignment-free maximum likelihood method for phylogenetic tree construction and shows it is competitive with existing alignment-free tools.

GAGER identifies key transcription factors to restore gene expression from a source to target state across multiple datasets, improving similarity between healthy and diseased states.

This paper investigates species tree terraces caused by missing data, showing they can improve summary method accuracy and branch support computation.

RNA-DCGen generates RNA sequences with specific structural or functional properties using a language model, outperforming random baselines in structure prediction.

This study conducts GWAS on 7 yield-related traits in 183 Bangladeshi rice landraces, identifying chromosomal regions and genes associated with grain shape and leaf traits.

This paper introduces scGIST, a deep learning method for designing spatial transcriptomics panels that prioritizes genes of interest while maintaining accuracy in cell type detection.

This paper introduces a probabilistic clustering method for scRNA-seq data that handles dropouts and does not require prior marker gene information, outperforming existing methods on six datasets.

Figbird fills gaps in draft genome assemblies using a probabilistic method with EM algorithm, outperforming existing tools in accuracy and error reduction.

SWALO improves genome assembly by using likelihood-based scaffolding, achieving more correct joins and fewer errors than existing methods.

The paper presents a faster implementation of an alignment-free association mapping method using k-mers, demonstrating improved performance on an E. coli dataset while maintaining accuracy.

This study introduces the concept of phylogenomic terraces in species tree estimation, showing that multiple species trees can have identical optimization scores under incomplete lineage sorting.

kRISP-meR designs CRISPR/Cas9 guide RNAs without a reference genome, achieving specificity similar to reference-based tools.

The paper reports the first reference genome assembly of the Black Bengal goat using de novo assembly and structural annotations.

The paper investigates whether multi-objective MSA formulations improve phylogenetic tree estimation and finds they do, outperforming single-objective methods.

This paper introduces an alignment-free method for genome-wide association studies using k-mer counts, demonstrating its ability to detect associations with structural variations and sequences absent from reference genomes.