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BEENE: deep learning-based nonlinear embedding improves batch effect estimation.

, , , and . Bioinform., (August 2023)

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Estimating Optimal Species Trees from Incomplete Gene Trees Under Deep Coalescence., and . J. Comput. Biol., 19 (6): 591-605 (2012)SAINT: self-attention augmented inception-inside-inception network improves protein secondary structure prediction., , , and . Bioinform., 36 (17): 4599-4608 (2020)QT-GILD: Quartet Based Gene Tree Imputation Using Deep Learning Improves Phylogenomic Analyses Despite Missing Data., , , , , and . RECOMB, volume 13278 of Lecture Notes in Computer Science, page 159-176. Springer, (2022)Gene tree parsimony for incomplete gene trees: addressing true biological loss., and . Algorithms Mol. Biol., 13 (1): 1:1-1:12 (2018)ASTRAL: genome-scale coalescent-based species tree estimation., , , , , and . Bioinform., 30 (17): 541-548 (2014)wQFM: highly accurate genome-scale species tree estimation from weighted quartets., , , , and . Bioinform., 37 (21): 3734-3743 (2021)Multiobjective Formulation of Multiple Sequence Alignment for Phylogeny Inference., , , , and . IEEE Trans. Cybern., 52 (5): 2775-2786 (2022)Fast and Accurate Branch Support Calculation for Distance-Based Phylogenetic Placements., , , , and . RECOMB-CG, volume 13234 of Lecture Notes in Computer Science, page 33-51. Springer, (2022)Gene Tree Parsimony for Incomplete Gene Trees., and . WABI, volume 88 of LIPIcs, page 2:1-2:13. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2017)Inferring Optimal Species Trees Under Gene Duplication and Loss., , and . Pacific Symposium on Biocomputing, page 250-261. World Scientific Publishing, (2013)