Bayesian clustering

The results of "Morphological and molecular characterization of Croatian carob tree (Ceratonia siliqua L.) germplasm" morphological and AFLP variability of 120 plants of carob tree (Ceratonia siliqua L.), collected from 12 different locations (10 biological replicates for each location) on the coast and islands of the southern Croatian Adriatic, indicate high molecular and morphological variability among these carob populations.

28p lyhuyenthu 31-01-2023 11 2   Download

Micro-level statistics on child undernutrition are highly prioritized by stakeholders for measuring and monitoring progress on the sustainable development goals. In this regard district-representative data were collected in the Bangladesh Multiple Indicator Cluster Survey 2019 for identifying localised disparities.

21p viferrari 28-11-2022 11 2   Download

Lecture Data mining: Lesson 1. The main topics covered in this chapter include: data warehouses and OLAP (On Line Analytical Processing); association rules mining; clustering - hierarchical and partition approaches; classification - decision trees and bayesian classifiers; sequential pattern mining;... Please refer to the content of document.

38p tieuvulinhhoa 22-09-2022 12 4   Download

This book "Data mining: Concepts and Techniques (Third edition)" is an extensive and detailed guide to the principal ideas, techniques and technologies of data mining. The book is organised in 13 substantial chapters, each of which is essentially standalone, but with useful references to the book’s coverage of underlying concepts. Please refer to the content of part 2 of book.

377p britaikridanik 05-07-2022 18 5   Download

This new textbook "Pattern Recognition and Machine Learning" reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first year PhD students, as well as researchers and practitioners, and assumes no previous knowledge of pattern recognition or machine learning concepts. Please refer to the content of part 2 of book.

380p britaikridanik 05-07-2022 24 4   Download

Measurements of single-cell methylation are revolutionizing our understanding of epigenetic control of gene expression, yet the intrinsic data sparsity limits the scope for quantitative analysis of such data.

15p vigalileogalilei 27-02-2022 8 1   Download

Using whole genome sequence (WGS) data, we assess two methods for detecting mixed infection: (i) a combination of the number of heterozygous sites and the proportion of heterozygous sites to total SNPs, and (ii) Bayesian model-based clustering of allele frequencies from sequencing reads at heterozygous sites.

15p vitzuyu2711 29-09-2021 7 1   Download

MicroRNA regulation is fundamentally responsible for fine-tuning the whole gene network in human and has been implicated in most physiological and pathological conditions. Studying regulatory impact of microRNA on various cellular and disease processes has resulted in numerous computational tools that investigate microRNA-mRNA interactions through the prediction of static binding site highly dependent on sequence pairing.

11p vitzuyu2711 29-09-2021 14 1   Download

One of the major challenges in microbial studies is detecting associations between microbial communities and a specific disease. A specialized feature of microbiome count data is that intestinal bacterial communities form clusters called as “enterotype”, which are characterized by differences in specific bacterial taxa, making it difficult to analyze these data under health and disease conditions.

13p visilicon2711 20-08-2021 10 1   Download

Time course data from microarrays and high-throughput sequencing experiments require simple, computationally efficient and powerful statistical models to extract meaningful biological signal, and for tasks such as data fusion and clustering.

12p viwyoming2711 16-12-2020 7 0   Download

Accurate genotype calling is a pre-requisite of a successful Genome-Wide Association Study (GWAS). Although most genotyping algorithms can achieve an accuracy rate greater than 99% for genotyping DNA samples without copy number alterations (CNAs), almost all of these algorithms are not designed for genotyping tumor samples that are known to have large regions of CNAs.

12p vikentucky2711 26-11-2020 6 0   Download

The complexity of biological data related to the genetic origins of tumour cells, originates significant challenges to glean valuable knowledge that can be used to predict therapeutic responses. In order to discover a link between gene expression profiles and drug responses, a computational framework based on Consensus p-Median clustering is proposed.

19p vikentucky2711 26-11-2020 16 1   Download

With recent development in sequencing technology, a large number of genome-wide DNA methylation studies have generated massive amounts of bisulfite sequencing data. The analysis of DNA methylation patterns helps researchers understand epigenetic regulatory mechanisms.

12p vikentucky2711 26-11-2020 17 1   Download

Flow cytometry is a widespread single-cell measurement technology with a multitude of clinical and research applications. Interpretation of flow cytometry data is hard; the instrumentation is delicate and can not render absolute measurements, hence samples can only be interpreted in relation to each other while at the same time comparisons are confounded by inter-sample variation.

16p vioklahoma2711 19-11-2020 7 1   Download

Detecting patterns in high-dimensional multivariate datasets is non-trivial. Clustering and dimensionality reduction techniques often help in discerning inherent structures. In biological datasets such as microbial community composition or gene expression data, observations can be generated from a continuous process, often unknown.

15p viflorida2711 30-10-2020 9 1   Download

Conventional phylogenetic clustering approaches rely on arbitrary cutpoints applied a posteriori to phylogenetic estimates. Although in practice, Bayesian and bootstrap-based clustering tend to lead to similar estimates, they often produce conflicting measures of confidence in clusters.

16p viconnecticut2711 28-10-2020 6 1   Download

Bayesian clustering algorithms, in particular those utilizing Dirichlet Processes (DP), return a sample of the posterior distribution of partitions of a set. However, in many applied cases a single clustering solution is desired, requiring a ’best’ partition to be created from the posterior sample.

10p viconnecticut2711 28-10-2020 13 1   Download

As the barriers to incorporating RNA sequencing (RNA-Seq) into biomedical studies continue to decrease, the complexity and size of RNA-Seq experiments are rapidly growing. Paired, longitudinal, and other correlated designs are becoming commonplace, and these studies offer immense potential for understanding how transcriptional changes within an individual over time differ depending on treatment or environmental conditions.

20p vicolorado2711 22-10-2020 12 0   Download

The fragmentation channels probabilities obtained as a function of the excitation energy, were compared with the experimental data at the Orsay Tandem. The deposited energy distributions were adjusted so that the experimental measurements were optimally reproduced. Two algorithms were used: Non-Negative Least Squares and Bayesian backtracing. The comparison of the theoretical and experimental probabilities shows a good global agreement. Both algorithms result in deposited energy distributions showing peaks.

12p capheny 28-02-2020 19 0   Download

This paper proposes a procedural pipeline for wind forecasting based on clustering and regression. First, the data are clustered into groups sharing similar dynamic properties. Then, data in the same cluster are used to train the neural network that predicts wind speed. For clustering, a hidden Markov model (HMM) and the modified Bayesian information criteria (BIC) are incorporated in a new method of clustering time series data.

16p dieutringuyen 07-06-2017 35 2   Download