We present QNet, a method for constructing split networks from weighted quartet trees. QNet can be viewed as a quartet analogue of the distance-based Neighbor-Net (NNet) method for network construction. Just as NNet, QNet works by agglomeratively computing a collection of circular weighted splits of the taxa set which is subsequently represented by a planar split network. To illustrate the applicability of QNet, we apply it to a previously published Salmonella data set. We conclude that QNet can provide a useful alternative to NNet if distance data are not available or a character-based approach is preferred. Moreover, it can be used as an aid for determining when a quartet-based tree-building method may or may not be appropriate for a given data set. QNet is freely available for download.
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http://dx.doi.org/10.1093/molbev/msl180 | DOI Listing |
Chaos
January 2025
College of Computer Science and Software Engineering, Shenzhen University, Guangdong 518060, China.
This paper considers the selection and optimization of drive nodes based on the controllability of multilayer networks. The intra-layer network topologies are arbitrary, and the node dynamics are linear time-invariant dynamical systems. The study focuses on the number and selection of drive nodes in a special class of drive-response networks.
View Article and Find Full Text PDFTrop Anim Health Prod
January 2025
Livestock Production and Management Section, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, Uttar Pradesh, 243 122, India.
Dry matter intake (DMI) determination is essential for effective management of meat goats, especially in optimizing feed utilization and production efficiency. Unfortunately, farmers often face challenges in accurately predicting DMI which leads to wastage of feed and an increase in the cost of production. This investigation aimed to predict DMI in Black Bengal goats by using body weight (BW), body condition score (BCS), average daily gain (ADG), and metabolic body weight (MBW) by applying an artificial neural network (ANN) model.
View Article and Find Full Text PDFPlant Cell Rep
January 2025
Laboratory of Cell & Molecular Biology, Institute of Vegetable Science, Zhejiang University, Hangzhou, China.
A high-throughput sequencing identified 1283 lncRNAs in anthers at different stages in Arabidopsis and their relationship with protein-coding genes and miRNAs during anther and pollen development were analyzed. Long non-coding RNAs (lncRNAs) are important regulatory molecules involved in various biological processes. However, their roles in male reproductive development and interactions with miRNAs remained elusive.
View Article and Find Full Text PDFTransplantation
January 2025
University of Zurich, Wyss Translational Center, Zurich, Switzerland.
Background: Early allograft dysfunction (EAD) affects outcomes in liver transplantation (LT). Existing risk models developed for deceased-donor LT depend on posttransplant factors and fall short in living-donor LT (LDLT), where pretransplant evaluations are crucial for preventing EAD and justifying the donor's risks.
Methods: This retrospective study analyzed data from 2944 adult patients who underwent LDLT at 17 centers between 2016 and 2020.
mSphere
January 2025
Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Coronaviruses (CoV) emerge suddenly from animal reservoirs to cause novel diseases in new hosts. Discovered in 2012, the Middle East respiratory syndrome coronavirus (MERS-CoV) is endemic in camels in the Middle East and is continually causing local outbreaks and epidemics. While all three newly emerging human CoVs from the past 20 years (SARS-CoV, SARS-CoV-2, and MERS-CoV) cause respiratory disease, each CoV has unique host interactions that drive differential pathogeneses.
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