Filters








10,845 Hits in 5.5 sec

Probabilistic drug connectivity mapping

Juuso A Parkkinen, Samuel Kaski
2014 BMC Bioinformatics  
The aim of connectivity mapping is to match drugs using drug-treatment gene expression profiles from multiple cell lines.  ...  This can be viewed as an information retrieval task, with the goal of finding the most relevant profiles for a given query drug.  ...  GFA scales to an arbitrary number of data sources, and the Bayesian probabilistic modeling makes it possible to cope with the biggest problem of gene expression data, the "large p small n" problem of having  ... 
doi:10.1186/1471-2105-15-113 pmid:24742351 pmcid:PMC4011783 fatcat:mbxzgdvc6jgx3l6i47jufpcvqi

Probabilistic retrieval and visualization of biologically relevant microarray experiments

J. Caldas, N. Gehlenborg, A. Faisal, A. Brazma, S. Kaski
2009 Bioinformatics  
We introduce novel retrieval methods that incorporate the actual gene expression measurements into the search process, along with visualization tools for interpreting and exploring the results [2].  ...  Our approach allows search within a gene expression database to be driven by actual measurement data.  ...  NG is supported by a PhD fellowship of the European Molecular Biology Laboratory (EMBL).  ... 
doi:10.1093/bioinformatics/btp215 pmid:19477980 pmcid:PMC2687969 fatcat:w4m3su325nh3nhqikouuohjthu

Probabilistic retrieval and visualization of biologically relevant microarray experiments

José Caldas, Nils Gehlenborg, Ali Faisal, Alvis Brazma, Samuel Kaski
2009 BMC Bioinformatics  
We introduce novel retrieval methods that incorporate the actual gene expression measurements into the search process, along with visualization tools for interpreting and exploring the results [2].  ...  Our approach allows search within a gene expression database to be driven by actual measurement data.  ...  NG is supported by a PhD fellowship of the European Molecular Biology Laboratory (EMBL).  ... 
doi:10.1186/1471-2105-10-s13-p1 fatcat:u4o2wgmarjb5flo7at4kmi3fp4

Modelling-based experiment retrieval: a case study with gene expression clustering

Paul Blomstedt, Ritabrata Dutta, Sohan Seth, Alvis Brazma, Samuel Kaski
2016 Bioinformatics  
For retrieval of gene expression experiments, we use a probabilistic model called product partition model, which induces a clustering of genes that show similar expression patterns across a number of samples  ...  In the context of gene expression experiments, most methods retrieve gene expression profiles, requiring each experiment to be expressed as a single profile, typically of case vs. control.  ...  Acknowledgement The authors would like to thank Ugis Sarkans for providing useful information about Expression Atlas.  ... 
doi:10.1093/bioinformatics/btv762 pmid:26740526 fatcat:zscvacmfsnebbhiiix7oxshaau

Dimensionality Reduction for Data Visualization [Applications Corner]

Samuel Kaski, Jaakko Peltonen
2011 IEEE Signal Processing Magazine  
In the gene expression retrieval case of Figure 3 , the data were expressions of a priori defined gene sets, quantized into counts, and the probabilistic model was the discrete principal component analysis  ...  Let's assume that in experiment i data g i have been measured; in the concrete case below g i will be a differential gene expression vector, where g ij is expression level of gene or gene set j compared  ... 
doi:10.1109/msp.2010.940003 fatcat:2rufhzzxpjevbc6zf3pbuykize

SpaCEM3: a software for biological module detection when data is incomplete, high dimensional and dependent

M. Vignes, J. Blanchet, D. Leroux, F. Forbes
2011 Bioinformatics  
Conflict of Interest: none declared.  ...  The SpaCEM 3 software (Spatial Clustering with EM and Markov Models) provides efficient statistical tools to deal with hightroughput biological data such as gene expression data.  ...  In a gene expression context, such interactions either come from prior knowledge or from measures like two-hybrid experiments.  ... 
doi:10.1093/bioinformatics/btr034 pmid:21296754 pmcid:PMC3051335 fatcat:j7mukelnabge7ee6kbdbzctxyu

Query-based biclustering of gene expression data using Probabilistic Relational Models

Hui Zhao, Lore Cloots, Tim Van den Bulcke, Yan Wu, Riet De Smet, Valerie Storms, Pieter Meysman, Kristof Engelen, Kathleen Marchal
2011 BMC Bioinformatics  
With the availability of large scale expression compendia it is now possible to view own findings in the light of what is already available and retrieve genes with an expression profile similar to a set  ...  Therefore, we developed ProBic, a query-based biclustering strategy based on Probabilistic Relational Models (PRMs) that exploits the use of prior distributions to extract the information contained within  ...  An overview of the ProBic Probabilistic Relational Model is shown in Figure 1 : it contains the classes Gene, Array and Expression.  ... 
doi:10.1186/1471-2105-12-s1-s37 pmid:21342568 pmcid:PMC3044293 fatcat:boj4poifyzfgnbnmkmopa7o5sa

Generating gene summaries from biomedical literature: A study of semi-structured summarization

Xu Ling, Jing Jiang, Xin He, Qiaozhu Mei, Chengxiang Zhai, Bruce Schatz
2007 Information Processing & Management  
Among all the proposed methods for sentence extraction, a probabilistic language modeling approach that models gene context performs the best.  ...  We evaluate the proposed methods using a test set with 20 genes.  ...  Among our proposed methods, although vector space model generally performs comparably with most probabilistic approaches, the probabilistic model with gene context analysis is the best by most of the evaluation  ... 
doi:10.1016/j.ipm.2007.01.018 fatcat:kusyzyzdkzbxjjblnksgznyyou

Toward Computational Cumulative Biology by Combining Models of Biological Datasets

Ali Faisal, Jaakko Peltonen, Elisabeth Georgii, Johan Rung, Samuel Kaski, Xiaoning Qian
2014 PLoS ONE  
By using the data-driven decomposition we identify a network of interrelated datasets from a large annotated human gene expression atlas.  ...  We introduce the idea of a modeling-based dataset retrieval engine designed for relating a researcher's experimental dataset to earlier work in the field.  ...  Acknowledgments We thank Matti Nelimarkka and Tuukka Ruotsalo for helping with citation data.  ... 
doi:10.1371/journal.pone.0113053 pmid:25427176 pmcid:PMC4245117 fatcat:bnevembobbajtah3zq46mneeve

CellMeSH: Probabilistic Cell-Type Identification Using Indexed Literature [article]

Shunfu Mao, Yue Zhang, Georg Seelig, Sreeram Kannan
2020 bioRxiv   pre-print
CellMeSH combines a database of gene-cell type associations with a probabilistic method for database querying.  ...  Measured single-cell transcriptomes are grouped by similarity and the resulting clusters are mapped to cell types based on cluster-specific gene expression patterns.  ...  The majority of these methods follow a machine learning approach, by first training a model based on the prior knowledge, and then utilizing the trained model either to classify the input gene expression  ... 
doi:10.1101/2020.05.29.124743 fatcat:va6t4eo7avchnjprqi564j4dda

Hierarchical Generative Biclustering for MicroRNA Expression Analysis [chapter]

José Caldas, Samuel Kaski
2010 Lecture Notes in Computer Science  
Clustering methods are a useful and common first step in gene expression studies, but the results may be hard to interpret.  ...  The formulation additionally offers a natural information retrieval relevance measure that allows relating samples in a principled manner.  ...  Information Retrieval Generative models offer a natural measure of pairwise object relevance. Consider an arbitrary probabilistic model parameterized by θ with input data X.  ... 
doi:10.1007/978-3-642-12683-3_5 fatcat:5in23a7dqrb7zfzpvbclmomkji

Hierarchical Generative Biclustering for MicroRNA Expression Analysis

José Caldas, Samuel Kaski
2011 Journal of Computational Biology  
Clustering methods are a useful and common first step in gene expression studies, but the results may be hard to interpret.  ...  The formulation additionally offers a natural information retrieval relevance measure that allows relating samples in a principled manner.  ...  Information Retrieval Generative models offer a natural measure of pairwise object relevance. Consider an arbitrary probabilistic model parameterized by θ with input data X.  ... 
doi:10.1089/cmb.2010.0256 pmid:21385032 fatcat:k35p5b7atvbkjpehyrrd3zwlf4

Evaluation of Stemming, Query Expansion and Manual Indexing Approaches for the Genomic Task

Samir Abdou, Jacques Savoy, Patrick Ruch
2005 Text Retrieval Conference  
Finally, we illustrate how the use of various query expansion techniques can impairs retrieval performance.  ...  We design a domain-specific query expansion scheme and compare it with the more classic Rocchio approach.  ...  IR MODELS In order to obtain a broader view of the relative merits of the various retrieval models, we analyzed nine different vector-space schemes and two probabilistic models.  ... 
dblp:conf/trec/AbdouSR05 fatcat:c6rsaclu65ecblk4aceleuexxm

Mining the Biomedical Literature in the Genomic Era: An Overview

Hagit Shatkay, Ronen Feldman
2003 Journal of Computational Biology  
the interrelated roles of various genes, proteins, and chemical reactions in cells and organisms.  ...  It surveys the disciplines involved in unstructured-text analysis, categorizes current work in biomedical literature mining with respect to these disciplines, and provides examples of text analysis methods  ...  HS was supported by an NIH IRTA fellowship while developing GenTheme, and was a member of the Informatics Research group at Celera/ABI when writing this article.  ... 
doi:10.1089/106652703322756104 pmid:14980013 fatcat:vbwcpl66ujhqdgq4wdjtllbg5e

NATbox: a network analysis toolbox in R

Shweta S Chavan, Michael A Bauer, Marco Scutari, Radhakrishnan Nagarajan
2009 BMC Bioinformatics  
NATbox provides a menu-driven GUI for modelling and analysis of FRs from gene expression profiles.  ...  statistical tools for modelling FRs in the form of acyclic networks from gene expression profiles and their subsequent analysis.  ...  The results of text retrieval on gene expression data from [4] is shown in Fig. 4 . Conclusion Modelling and analysis of gene expression networks is an area of active research.  ... 
doi:10.1186/1471-2105-10-s11-s14 pmid:19811679 pmcid:PMC3152789 fatcat:e3gowkycqfgzzmwfoflxgj3wum
« Previous Showing results 1 — 15 out of 10,845 results