To construct a phylogenetic tree or phylogenetic network for describing the evolutionary history of a set of species is a well-studied problem in computational biology. One previously proposed method to infer a phylogenetic tree/network for a large set of species is by merging a collection of known smaller phylogenetic trees on overlapping sets of species so that no (or as little as possible) branching information is lost. However, little work has been done so far on inferring a phylogenetic tree/network from a specified set of trees when in addition, certain evolutionary relationships among the species are known to be highly unlikely. In this paper, we consider the problem of constructing a phylogenetic tree/network which is consistent with all of the rooted triplets in a given set C and none of the rooted triplets in another given set F. Although NP-hard in the general case, we provide some efficient exact and approximation algorithms for a number of biologically meaningful variants of the problem.
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http://dx.doi.org/10.1142/s0219720006001709 | DOI Listing |
Environ Microbiol Rep
October 2024
Université du Littoral Côte d'Opale, UR 4492, Unité de Chimie Environnementale et Interactions sur le Vivant (UCEIV), Calais Cedex, France.
J Chem Theory Comput
October 2024
Department of Chemistry, Life Science and Environmental Sustainability, Università di Parma, 43124 Parma, Italy.
Anal Bioanal Chem
November 2024
Institute of Chemistry and Technology of Environmental Protection, Faculty of Chemistry, Brno University of Technology, Purkyňova 118, 612 00, Brno, Czech Republic.
Pharmaceuticals released into the aquatic and soil environments can be absorbed by plants and soil organisms, potentially leading to the formation of unknown metabolites that may negatively affect these organisms or contaminate the food chain. The aim of this study was to identify pharmaceutical metabolites through a triplet approach for metabolite structure prediction (software-based predictions, literature review, and known common metabolic pathways), followed by generating in silico mass spectral libraries and applying various mass spectrometry modes for untargeted LC-qTOF analysis. Therefore, Eisenia fetida and Lactuca sativa were exposed to a pharmaceutical mixture (atenolol, enrofloxacin, erythromycin, ketoprofen, sulfametoxazole, tetracycline) under hydroponic and soil conditions at environmentally relevant concentrations.
View Article and Find Full Text PDFJ Phys Chem B
August 2024
Department of Chemistry, Georgia State University, Atlanta, Georgia 30302, United States.
The use of flavins and flavoproteins in photocatalytic, sensing, and biotechnological applications has led to a growing interest in computationally modeling the excited-state electronic structure and photophysics of flavin. However, there is limited consensus regarding which computational methods are appropriate for modeling flavin's photophysics. We compare the energies of low-lying excited states of flavin computed with time-dependent density functional theory (TD-DFT), equation-of-motion coupled cluster (EOM-EE-CCSD), scaled opposite-spin configuration interaction [SOS-CIS(D)], multiconfiguration pair-density functional theory (MC-PDFT), and several multireference perturbation theory (MR-PT2) methods.
View Article and Find Full Text PDFNew Phytol
July 2024
Department of Plant Biotechnology and Bioinformatics, Ghent University, 9052, Ghent, Belgium.
Hybridization, the process of crossing individuals from diverse genetic backgrounds, plays a pivotal role in evolution, biological invasiveness, and crop breeding. At the transcriptional level, hybridization often leads to complex nonadditive effects, presenting challenges for understanding its consequences. Although standard transcriptomic analyses exist to compare hybrids to their progenitors, such analyses have not been implemented in a software package, hindering reproducibility.
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