A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2008; you can also visit the original URL.
The file type is application/pdf.
Filters
Boolean Property Encoding for Local Set Pattern Discovery: An Application to Gene Expression Data Analysis
[chapter]
2005
Lecture Notes in Computer Science
Preserved Fulltext
In the domain of gene expression data analysis, several researchers have recently emphasized the promising application of local pattern (e.g., association rules, closed sets) discovery techniques from ...
To take the most from local set pattern mining approaches, a needed step concerns gene expression property encoding (e.g., over-expression). ...
The authors want to thank Céline Robardet, Sylvain Blachon and Olivier Gandrillon for the pre-processing of the SAGE data set, and Sophie Rome for her participation to microarray data preparation. ...
doi:10.1007/11504245_8
fatcat:asxz7ttcnbfojlxeeac5owhqla
Redescription Mining and Applications in Bioinformatics
[chapter]
2009
Chapman & Hall/CRC Data Mining and Knowledge Discovery Series
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2011; you can also visit the original URL.
The file type is application/pdf.
We present algorithms for redescription mining based on formal concept analysis and applications of redescription mining to multiple biological datasets. ...
Given a set of biological objects (e.g., genes, proteins) and a collection of descriptors defined over this set, the goal of redescription mining is to use the given descriptors as a vocabulary and find ...
The key property of a redescription, like most data mining patterns, is that it must be falsifiable in some interpretation (dataset). ...
doi:10.1201/9781420086850.ch22
fatcat:lelc5qyxrzggnkuahgu7ticihe
Integrated analysis of gene expression by Association Rules Discovery
2006
BMC Bioinformatics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
In this study we present a method for the integrative analysis of microarray data based on the Association Rules Discovery data mining technique. ...
The approach integrates gene annotations and expression data to discover intrinsic associations among both data sources based on co-occurrence patterns. ...
We also want to thank the reviewers of this paper for their constructive comments that have aided in improving this work. ...
doi:10.1186/1471-2105-7-54
pmid:16464256
pmcid:PMC1386712
fatcat:eukxnzloozdz3pr7ibtyk4sa2a
Large-Scale Differentiable Causal Discovery of Factor Graphs
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
RNA sequencing data set with hundreds of genetic interventions. ...
We propose Differentiable Causal Discovery of Factor Graphs (DCD-FG), a scalable implementation of f-DAG constrained causal discovery for high-dimensional interventional data. ...
She was an SAB member of ThermoFisher Scientific, Syros Pharmaceuticals, Neogene Therapeutics, and Asimov until July 31st, 2020; she has been an employee of Genentech since August 1st, 2020, and has equity ...
arXiv:2206.07824v1
fatcat:vsiwsimwvbhahmbeipjmskuime
MDL4BMF
2014
ACM Transactions on Knowledge Discovery from Data
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
We discuss how to construct an appropriate encoding: starting from a simple and intuitive approach, we arrive at a highly efficient data-to-model-based encoding for BMF. ...
We extend an existing algorithm for BMF to use MDL to identify the best Boolean matrix factorization, analyze the complexity of the problem, and perform an extensive experimental evaluation to study its ...
We discussed how to construct an appropriate encoding for BMF, starting by introducing simple and intuitive approaches, and progressing to a highly efficient typed DtM-based encoding. ...
doi:10.1145/2601437
fatcat:grz322vafjaxthpxdohnonw74y
On the discovery of association rules by means of evolutionary algorithms
2011
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Association rule learning is a data mining task that tries to discover interesting relations between variables in large databases. ...
A review of association rule learning is presented that focuses on the use of evolutionary algorithms not only applied to Boolean variables but also to categorical and quantitative ones. ...
Thus, the following applications can be found: 66 apply knowledge discovery in the form of ARs to the analysis of gene expression data in order to identify patterns of genes and regulatory network. ...
doi:10.1002/widm.18
fatcat:hblu7qeye5ac3it5f3n6yma7wa
Supporting scientific knowledge discovery with extended, generalized Formal Concept Analysis
2016
Expert systems with applications
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
techniques that support scientific hypothesis-making and discovery in a range of domains: semiring theory, perceptual studies, natural language semantics, and gene expression data analysis. ...
In this paper we fuse together the Landscapes of Knowledge of Wille's and Exploratory Data Analysis by leveraging Formal Concept Analysis (FCA) to support data-induced scientific enquiry and discovery. ...
Acknowledgments FJVA and AP were partially supported by EU FP7 project LiMo-SINe (contract 288024) for this research. ...
doi:10.1016/j.eswa.2015.09.022
fatcat:l7fequzx65hkxkrota5umcgtoa
DYNAMIC PROGRAMMING STRATEGIES FOR ANALYZING BIOMOLECULAR SEQUENCES
[chapter]
2004
Selected Topics in Post-Genome Knowledge Discovery
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2005; you can also visit the original URL.
The file type is application/pdf.
an optimal solution, and the traceback for delivering an optimal solution. ...
Here we introduce these basic ideas by developing dynamic-programming solutions for problems from different application areas. ...
The author would like to thank Drs. Louis Chen and Louxin Zhang for their support and encouragement. ...
doi:10.1142/9789812794840_0001
fatcat:d2c7nvvc75fwbpmhrak74vhm4u
Pattern discovery in gene regulation; designing an analysis environment
1993
Proceedings. International Conference on Intelligent Systems for Molecular Biology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2015; you can also visit the original URL.
The file type is application/pdf.
The analysis tools will serve as an ideal environment for 'dry biology' experimentation and provide a context for 'wet' experiments. ...
'Wet lab' biology has an inherent difficulty in considering multiple components within one experimental set-up. ...
Analysis environment, wCS supports the beginning of an analysis environment: an exploratory navigation across multiple sources to discover patterns within the data and literature. ...
pmid:7584365
fatcat:5p6cymynivc6ljvg5tua32uyjy
Advanced Systems Biology Methods in Drug Discovery and Translational Biomedicine
2013
BioMed Research International
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
The systems biology methods and applications covered in this review provide a framework for addressing disease mechanism and approaching drug discovery, which will facilitate the translation of research ...
gene prediction. ...
Furthermore, numerous systems biology approaches based on gene expression data for in silico drug repositioning have been published [62, 63] . ...
doi:10.1155/2013/742835
pmid:24171171
pmcid:PMC3792523
fatcat:nhsv3ig7vzgspjhnzkaj3pwypm
Model order selection for boolean matrix factorization
2011
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '11
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
We extend an existing algorithm for BMF to use MDL to identify the best Boolean matrix factorization, analyze the complexity of the problem, and perform an extensive experimental evaluation to study its ...
We formulate the description length function for BMF in generalmaking it applicable for any BMF algorithm. ...
As such, BMF essentially describes the data with a set of patterns. Therefore, pattern set mining techniques are related. ...
doi:10.1145/2020408.2020424
dblp:conf/kdd/MiettinenV11
fatcat:pb7xvqypa5ayff5gvwis4uc2wu
Genomics, "Discovery Science," Systems Biology, and Causal Explanation: What Really Works?
2015
Perspectives in biology and medicine
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
alternatives, such as "discovery science," some productions of the ENCODE project, and aspects of large data set systems biology. ...
Their properties emerge in high relief when contrasted (as an example) to a recent, system-wide, predictive analysis of a developmental regulatory apparatus that was instead based directly on hypothesis-driven ...
(also known as discovery-based science) is a scientific methodology which emphasizes analysis of large volumes of experimental data with the goal of finding new patterns or correlations, leading to hypothesis ...
doi:10.1353/pbm.2015.0025
pmid:26750600
fatcat:tpxw5j5hmvf73m5y5wvjju7cxu
Evolving connectionist systems for knowledge discovery from gene expression data of cancer tissue
2003
Artificial Intelligence in Medicine
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Microarray techniques have made it possible to observe the expression of thousands of genes simultaneously. They have recently been applied to study gene expression patterns in tissue samples. ...
Statistical and machine learning methods have recently been used to classify cancer tissue based on gene expression data. ...
Acknowledgements We would like to thank the reviewers for their constructive comments and Bronwyn Carlisle for proof-reading. ...
doi:10.1016/s0933-3657(03)00063-0
pmid:12893118
fatcat:e4c2dcu7qbdjdprbze63jecisy
Selfish: Discovery of Differential Chromatin Interactions via a Self-Similarity Measure
[article]
2019
bioRxiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
A fundamental problem inthe analysis of Hi-C data is how to compare two contact maps derived from Hi-C experiments. ...
:We present a novel method called Selfish for the comparative analysis of Hi-C data that takes advantage of the structural self-similarity in contact maps. ...
Then we computed the percentage of those genes having an expression fold change of two or greater. For the set of genes overlapping FIND's DCIs, 71.46% of them were over-expressed. ...
doi:10.1101/540708
fatcat:hbmcrt2phzb5ne3ynrzy2uig6m
Enhancing knowledge discovery via association-based evolution of neural logic networks
2006
IEEE Transactions on Knowledge and Data Engineering
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2007; you can also visit the original URL.
The file type is application/pdf.
Coupled with a sequential covering approach for generating a list of neulonets, the straightforward extraction of human-like logic rules from each neulonet provides an alternate perspective to the greater ...
This is due to the richness in logic expression inherent in the neulonet learning paradigm. ...
for extracting patterns from data and . the interpretation component that relates to the novelty, utility, and understanding of the mined patterns or rules. ...
doi:10.1109/tkde.2006.111
fatcat:wdesnhdmgzdm3jornrectecuom
« Previous
Showing results 1 — 15 out of 1,818 results