Rezwana Reaz

STEQ: A statistically consistent quartet distance based species tree estimation method

STEQ is a fast and accurate distance-based method for estimating species trees from gene trees, maintaining competitive accuracy while being asymptotically faster than existing methods.

Leveraging weighted quartet distributions for enhanced species tree inference from genome-wide data

This study evaluates weighted quartet methods for species tree inference, finding that GTF-based approaches outperform ASTRAL and SVDquartets in accuracy.

wQFM-TREE: highly accurate and scalable quartet-based species tree inference from gene trees

This paper introduces wQFM-TREE, a method for species tree inference that improves accuracy and scalability over existing methods like ASTRAL and wQFM.

QT-GILD: Quartet Based Gene Tree Imputation Using Deep Learning Improves Phylogenomic Analyses Despite Missing Data

QT-GILD improves species tree estimation by imputing missing quartets from incomplete gene trees using deep learning, enhancing accuracy despite data gaps.

wQFM: Statistically Consistent Genome-scale Species Tree Estimation from Weighted Quartets

The paper introduces wQFM, a method for estimating species trees from weighted quartets, showing it matches or improves upon existing methods in accuracy.

STELAR: A statistically consistent coalescent-based species tree estimation method by maximizing triplet consistency

STELAR estimates species trees from gene trees using a coalescent-based method that maximizes triplet consistency, achieving high accuracy and scalability.