Complete chloroplast genome sequences of Myristicaceae species with the comparative chloroplast genomics and phylogenetic relationships among them by Changli Mao, Fengliang Zhang, Xiaoqin Li, Tian Yang, Qi Zhao, Yu Wu

“…Phylogenetic analysis showed that all Knema species were clustered in the same group and formed a sister clade with Myristica species support by both high maximum likelihood bootstrap values and Bayesian posterior probabilities; among Horsfieldia species, Horsfieldia amygdalina (Wall.) …”
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Multimodal sensor data fusion for in-situ classification of animal behavior using accelerometry and GNSS data by Reza Arablouei, Ziwei Wang, Greg J. Bishop-Hurley, Jiajun Liu

“…The second approach is based on fusing the posterior probabilities predicted by two MLP classifiers. …”
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A Bayesian approach to estimate the probability of resistance to bedaquiline in the presence of a genomic variant. by Degefaye Zelalem Anlay, Emmanuel Rivière, Pham Hien Trang Tu, Steven Abrams, Annelies Van Rie

“…<h4>Methods</h4>Using published phenotype data for variants in Rv0678, atpE, pepQ and Rv1979c genes in 756 Mycobacterium tuberculosis isolates and survey data of the opinion of 33 experts, we applied Bayesian methods to estimate the posterior probability of bedaquiline resistance and corresponding 95% credible intervals.…”
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Complete mitochondrial genome of Tolypocladium sp. YFCC 1805002 isolated from Ophiocordyceps sinensis in Baima Snow Mountain, Southwestern China by Yanfang Liu, Dexiang Tang, Guodong Zhang, Mingxi Zhang, Yao Wang, Yuanbing Wang, Hong Yu

“…YFCC 1805002 is closely related to T. inflatum in the family Ophiocordycipitaceae with high credible support by Bayesian inference posterior probabilities (BI-PP = 100%). This study would facilitate the future research of genetics, evolution and medicine of cordycipitoid fungi.…”
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A hypotensive episode predictor for intensive care based on heart rate and blood pressure time series by Lee, J., Mark, Roger Greenwood

“…While individual gap sizes were evaluated independently, weighted posterior probabilities based on different gap sizes were also investigated. …”
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Phylogenetic evidence for the ancient Himalayan wolf: towards a clarification of its taxonomic status based on genetic sampling from western Nepal by Werhahn, G, Senn, H, Kaden, J, Joshi, J, Bhattarai, S, Kusi, N, Sillero-Zubiri, C, Macdonald, D

“…We then compare the genetic profile of the Himalayan wolf lineage found in northwestern Nepal with canid reference sequences from around the globe with maximum likelihood and Bayesian phylogeny building methods to demonstrate that the Himalayan wolf forms a distinct monophyletic clade supported by posterior probabilities/bootstrap for D-loop of greater than 0.92/85 and cytochrome b greater than 0.99/93. …”

Probabilistic treatment of expert judgment on aleatory and epistemic uncertainties associated with on-board vehicle hydrogen storage systems by Khalil, Y, Mosher, D

“…As new evidence becomes available, the aggregated probability can be Bayesian updated to generate a posterior probability distribution for the uncertain quantity or event of interest. …”

Repeated tests on serially correlated data by Geary, D, David Norman Geary

“…The possibility of using stopping rules based on posterior probabilities, rather than sequentially adjusted P values, is considered briefly in 2.1. …”

Phylogenetic relationships within the Genus Holothuria inferred from 16S Mitochondiral rRNA Gene Sequences by Kamarul Rahim Kamarudin, Aisyah Mohamed Rehan, Ridzwan Hashim, Gires Usup, Maryam Mohamed Rehan

“…Subgenera of Holothuria, Merthensiothuria and Metriatyla are monophyletic with strong bootstrap supports and posterior probabilities of clades, thus strengthening their morphological taxonomies. …”
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Phylogenetic and haplotype analyses offer insights towards conservation of pteroptyx tener olivier, 1907 (coleoptera: lampyridae) populations from Malaysia by Nur-Athirah ABDULLAH, Madihah HALIM, Mahadimenakbar DAWOOD, Izfa Riza HAZMI, Shahril Mohd. HUSIN, Norela Sulaiman, Salmah YAAKOP

“…A total of 50 sequences of P. tener were used in the Neighbour-Joining (NJ), Maximum Parsimony (MP), and Bayesian Inference (BI) phylogenetic analyses and successfully formed several distinct clades of West and East Malaysia (East Coast and West Coast of Peninsular Malaysia) with moderately to highly supported bootstrap values and posterior probabilities. Several haplotype analysis parameters are presented; low nucleotide diversity (PiT, 0.01893), haplotype number (Hn, 19), and high haplotype diversity (Hd, 0.89469). …”
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Balanced resuscitation and earlier mortality end points: bayesian post hoc analysis of the PROPPR trial by Rindi Uhlich, Joshua Richman, Omar Rokayak, Thomas Sensing, Emily Baird

“…The aim of this post hoc analysis of the PROPPR trial was to evaluate the impact of a balanced resuscitation strategy at early resuscitation time points using a Bayesian analytical framework.Methods Bayesian hierarchical models were created to assess mortality differences at the 1, 3, 6, 12, 18, and 24 hours time points between study cohorts. Posterior probabilities and Bayes factors were calculated for each time point.Results A 1:1:1 resuscitation displayed a 96%, 99%, 94%, 92%, 96%, and 94% probability for mortality benefit at 1, 3, 6, 12, 18, and 24 hours, respectively, when compared with a 1:1:2 approach. …”
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Cryptic diversity in a gastrointestinal acanthocephalan of New World primates from Costa Rica by Ernesto Rojas-Sánchez, Fabián Umaña-Blanco, Ana Jiménez-Rocha, Karen Vega-Benavides, Alejandro Medaglia, Alberto Solano-Barquero, Alicia Rojas, Mauricio Jiménez

“…Sequences obtained herein clustered separately with high posterior probabilities in a Bayesian Inference tree and showed 8.12% nucleotide differences when compared to P. elegans from Colombia. …”
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A Bayesian approach for constituent estimation in nucleic acid mixture models by Taichi Tomono, Taichi Tomono, Taichi Tomono, Satoshi Hara, Yusuke Nakai, Kazuma Takahara, Junko Iida, Junko Iida, Takashi Washio

“…Using Simulated Annealing, NUTS, and stochastic variational inference, we determine the parameters for each constituent number model and the maximum posterior probability. Finally, by comparing the maximum posterior probabilities between models, we select the optimal number of constituents and estimate the monoisotopic mass and ion counts under that scenario.…”
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Prospectivity Mapping for Magmatic-Related Seafloor Massive Sulfide on the Mid-Atlantic Ridge Applying Weights-of-Evidence Method Based on GIS by Lushi Liu, Jilong Lu, Chunhui Tao, Shili Liao

“…Seven zones with high posterior probabilities but without known hydrothermal fields were delineated as prospecting targets. …”
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Pleistocene population differentiation in the ant Myrmica scabrinodis (Hymenoptera: Formicidae) – a taxonomic borderline case by Bernhard Seifert

“…At the first hand, this seemed to justify considering the two clusters as separate species. The posterior probabilities of the type series when run as wild-card runs in a LDA were 0.9366 in M. rugulosoides, 0.9999 in M. martini, 0.0284 in M. scabrinodis and 0.0081 in M. pilosiscapus – allocating the former two to western cluster and the latter two to the eastern cluster. …”
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An Optimal Burn-In Policy for Cellular Phone Lithium-Ion Batteries Using a Feature Selection Strategy and Relevance Vector Machine by Jinsong Yu, Jie Yang, Diyin Tang, Jing Dai

“…Given the selected feature subset, the RVM is applied to classify batteries into two groups and simultaneously obtain the posterior probabilities. To achieve better discrimination performance with less risk, a new characteristic is extracted from the discharge profile. …”
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The FORCE Panel: An All-in-One SNP Marker Set for Confirming Investigative Genetic Genealogy Leads and for General Forensic Applications by Andreas Tillmar, Kimberly Sturk-Andreaggi, Jennifer Daniels-Higginbotham, Jacqueline Tyler Thomas, Charla Marshall

“…The WWII case results showed that the FORCE panel could predict first to fifth degree relationships with strong statistical support (likelihood ratios over 10,000 and posterior probabilities over 99.99%). To conclude, SNPs will be important for further advances in forensic DNA analysis. …”
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Bayesian Linear Seismic Inversion Integrating Uncertainty of Noise Level Estimation and Wavelet Extraction by Xiuwei Yang, Ningbo Mao, Peimin Zhu

“…For each realization, the corresponding posterior probability model of impedance was achieved by Bayesian linear inversion and the final posterior probability of the impedance model was obtained by integrating all the single posterior probabilities for each pair of wavelet and noise variance. …”
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Phylogenetics of native conifer species in Vietnam based on two chloroplast gene regions rbcL and matK by Mai Phuong Pham, Viet Ha Tran, Dinh Duy Vu, Quoc Khanh Nguyen, Syed Noor Muhammad Shah

“…The phylogenetic analyses using the Maximum likelihood (ML) and Bayesian inference (BI) bootstrap values obtained at the branching nodes of each species ranged from 62 to 100% (Maximum likelihood bootstrap - MLBS and Bayesian posterior probabilities - BPP) for the matK gene; from 66 to 100% (MLBS) and 60 to 100% (BPP) for the rbcL region. …”
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A simple plug-in bagging ensemble based on threshold-moving for classifying binary and multiclass imbalanced data by Collell Talleda, Guillem, Prelec, Drazen, Patil, Kaustubh R

“…Contrary to the other resampling methods, we preserve the natural class distribution of the data resulting in well-calibrated posterior probabilities. Additionally, we extend the proposed method to handle multiclass data. …”
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