* Indicates student co-author
Dodds, Zachary, Malia Morgan*, Lindsay Popowski*, Henry Coxe*, Caroline Coxe*, Kewei Zhou*, Eliot Bush, Ran Libeskind-Hadas. “Biology-based CS1: Results and Reflections, Ten Years In.” Proceedings of SIGCSE, 2021.
Abstract: For a decade, our institution has offered both a biology-based CS1 (CS1-B) and a traditional, breadth-based CS1. This project follows the paths of students in both courses—tracking their subsequent interests (what courses do the two groups choose afterwards?) and their grades in those courses. Within the biology-based cohort, we also contrast the futures of the students who chose a biology-themed introduction with the group who expressed no preference or requested the breadth-based approach. Even when student preference was not accommodated, equitable downstream performance results hold. We discuss the implications of these results, including the possibility that, like introductory writing, introductory computing is a professional literacy in which many disciplines have a stake.
LeMay, Matthew*, Ran Libeskind-Hadas, and Yi-Chieh Wu. “The Most Parsimonious Reconciliation Problem in the Presence of Incomplete Lineage Sorting and Hybridization is NP-Hard.” 21st International Workshop on Algorithms in Bioinformatics (WABI 2021), edited by Alessandra Carbone and Mohammed El-Kebir. Schloss Dagstuhl- Leibniz-Zentrum für Informatik, 2021.
Abstract: The maximum parsimony phylogenetic reconciliation problem seeks to explain incongruity between a gene phylogeny and a species phylogeny with respect to a set of evolutionary events. While the reconciliation problem is well-studied for species and gene trees subject to events such as duplication, transfer, loss, and deep coalescence, recent work has examined species phylogenies that incorporate hybridization and are thus represented by networks rather than trees. In this paper, we show that the problem of computing a maximum parsimony reconciliation for a gene tree and species network is NP-hard even when only considering deep coalescence. This result suggests that future work on maximum parsimony reconciliation for species networks should explore approximation algorithms and heuristics.
LeMay, Matthew*, Ran Libeskind-Hadas, and Yi-Chieh Wu. “A Polynomial-Time Algorithm for Minimizing the Deep Coalescence Cost for Level-1 Species Networks.” IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2021.
Abstract: Phylogenetic analyses commonly assume that the species history can be represented as a tree. However, in the presence of hybridization, the species history is more accurately captured as a network. Despite several advances in modeling phylogenetic networks, there is no known polynomial-time algorithm for parsimoniously reconciling gene trees with species networks while accounting for incomplete lineage sorting. To address this issue, we present a polynomial-time algorithm for the case of level-1 networks, in which no hybrid species is the direct ancestor of another hybrid species. This work enables more efficient reconciliation of gene trees with species networks, which in turn, enables more efficient reconstruction of species networks.
Liu*, Jingyi, Ross Mawhorter, Nuo Liu, Santi Santichaivekin*, Elliot Bush, and Ran Libeskind-Hadas. “Maximum Parsimony Reconciliation in the DTLOR Model.” BMC Bioinformatics, vol. 22, 2021, 394.
Abstract: Background Analyses of microbial evolution often use reconciliation methods. However, the standard duplication-transfer-loss (DTL) model does not account for the fact that species trees are often not fully sampled and thus, from the perspective of reconciliation, a gene family may enter the species tree from the outside. Moreover, within the genome, genes are often rearranged, causing them to move to new syntenic regions.
Santichaivekin*, Santi, Qing Yang*, Jingyi Liu*, Ross Mawhorter, Justin Jiang*, Trenton Wesley*, Yi-Chieh Wu, and Ran Libeskind-Hadas. “eMPRess: A systematic Cophylogeny Reconciliation Tool.” Bioinformatics, vol. 37, issue 16, 2021, pp. 2481-2482.
Abstract: We describe eMPRess, a software program for phylogenetic tree reconciliation under the duplication-transfer-loss model that systematically addresses the problems of choosing event costs and selecting representative solutions, enabling users to make more robust inferences.