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Hierarchical bayesian
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Integrating rare variation from trio family and case–control studies has successfully implicated specific genes contributing to risk of neurodevelopmental disorders (NDDs) including autism spectrum disorders (ASD), intellectual disability (ID), developmental disorders (DDs), and epilepsy (EPI). For schizophrenia (SCZ), however, while sets of genes have been implicated through the study of rare variation, only two risk genes have been identified.
22p
vioraclene
31-03-2024
5
2
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Genome-wide Association Studies (GWAS) are typically designed to identify phenotype-associated single nucleotide polymorphisms (SNPs) individually using univariate analysis methods. Though providing valuable insights into genetic risks of common diseases, the genetic variants identified by GWAS generally account for only a small proportion of the total heritability for complex diseases.
11p
vinarcissa
21-03-2023
3
1
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Determining factors associated with cholera disease in Ethiopia using Bayesian hierarchical modeling
Cholera is a diarrheal disease caused by infection of the intestine with the gram-negative bacteria Vibrio cholera. It is caused by the ingestion of food or water and infected all age groups. This study aimed at identifying risk factors associated with cholera disease in Ethiopia using the Bayesian hierarchical model.
10p
viferrari
29-10-2022
7
2
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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
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Various efforts have been made to elucidate the cooperating proteins involved in maintaining chromatin interactions; however, many are still unknown. Here, we present 3CPET, a tool based on a non-parametric Bayesian approach, to infer the set of the most probable protein complexes involved in maintaining chromatin interactions and the regions that they may control, making it a valuable downstream analysis tool in chromatin conformation studies.
16p
viaristotle
29-01-2022
10
0
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We present a generative model, Lux, to quantify DNA methylation modifications from any combination of bisulfite sequencing approaches, including reduced, oxidative, TET-assisted, chemical-modification assisted, and methylaseassisted bisulfite sequencing data.
22p
viaristotle
29-01-2022
7
0
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Traditional differential expression tools are limited to detecting changes in overall expression, and fail to uncover the rich information provided by single-cell level data sets. We present a Bayesian hierarchical model that builds upon BASiCS to study changes that lie beyond comparisons of means, incorporating built-in normalization and quantifying technical artifacts by borrowing information from spike-in genes.
14p
viaristotle
29-01-2022
14
0
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Alternative splicing is a biological process during gene expression that allows a single gene to code for multiple proteins. However, splicing patterns can be altered in some conditions or diseases. Here, we present BANDITS, a R/Bioconductor package to perform differential splicing, at both gene and transcript level, based on RNA-seq data.
13p
viarchimedes
26-01-2022
12
0
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We present Hierarchical Bayesian Analysis of Differential Expression and ALternative Splicing (HBA-DEALS), which simultaneously characterizes differential expression and splicing in cohorts. HBA-DEALS attains state of the art or better performance for both expression and splicing and allows genes to be characterized as having differential gene expression, differential alternative splicing, both, or neither.
20p
viarchimedes
26-01-2022
9
0
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Although human leukocyte antigen (HLA) genotyping based on amplicon, whole exome sequence (WES), and RNA sequence data has been achieved in recent years, accurate genotyping from whole genome sequence (WGS) data remains a challenge due to the low depth. Furthermore, there is no method to identify the sequences of unknown HLA types not registered in HLA databases.
11p
vitzuyu2711
29-09-2021
10
1
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The human microbiome forms very complex communities that consist of hundreds to thousands of different microorganisms that not only affect the host, but also participate in disease processes.
17p
vilichoo2711
25-06-2021
17
2
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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
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One of the goals of the Systems Biology community is to have a detailed map of all biological interactions in an organism. One small yet important step in this direction is the creation of biological networks from post-genomic data.
10p
vikentucky2711
24-11-2020
28
2
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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
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The Human Microbiome has been variously associated with the immune-regulatory mechanisms involved in the prevention or development of many non-infectious human diseases such as autoimmunity, allergy and cancer.
12p
vioklahoma2711
19-11-2020
12
1
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Group structures among genes encoded in functional relationships or biological pathways are valuable and unique features in large-scale molecular data for survival analysis. However, most of previous approaches for molecular data analysis ignore such group structures.
15p
vicoachella2711
27-10-2020
13
0
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High-throughput sequencing experiments, which can determine allele origins, have been used to assess genome-wide allele-specific expression. Despite the amount of data generated from high-throughput experiments, statistical methods are often too simplistic to understand the complexity of gene expression.
13p
vicolorado2711
23-10-2020
11
1
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MCMSeq: Bayesian hierarchical modeling of clustered and repeated measures RNA sequencing experiments
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
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Heterogeneity in the definition and measurement of complex diseases in Genome-Wide Association Studies (GWAS) may lead to misdiagnoses and misclassification errors that can significantly impact discovery of disease loci.
25p
vicolorado2711
22-10-2020
6
0
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A Bayesian approach with frequentist validity has been developed to support inferences derived from a BLevel A^ in vivo-in vitro correlation (IVIVC). Irrespective of whether the in vivo data reflect in vivo dissolution or absorption, the IVIVC is typically assessed using a linear regression model. Confidence intervals are generally used to describe the uncertainty around the model. While the confidence intervals can describe population-level variability, it does not address the individual-level variability.
16p
caothientrangnguyen
09-05-2020
27
0
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