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Comparison of Gene Co-expression Networks and Bayesian Networks
Comparison of Gene Co-expression Networks and Bayesian Networks

... and widely researched. Bilu and Linial’s [10] work proposes a hierarchical clustering through the metric “BLAST” which is a measure of similarity in genes. A functional prediction is then performed so as to validate the clustered genes. Yeast genes are studied using Bayesian Networks by Friedman, et ...
TKTL_luento3
TKTL_luento3

... • Results from heuristics are analyzed using proposed Bayes model • Evaluation of the results using the artificial data – estimate how well the obtained model predicts the future data sets – compare the models with DJS that uses also prior information ...
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slides2

... Idea: harness evolution/adaptation strategically for therapeutic/technological/scientific goals Model this as a 2-player 0-sum incomplete-information game between treater and opponent ...
Comp. Genomics
Comp. Genomics

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Baylor /Waco Comments - Texas Water Resources Institute
Baylor /Waco Comments - Texas Water Resources Institute

... of water sampling sites that should be included in assessment and a method for how to select the minimum number of water sampling sites. Inadequate sample site selection and numbers can limit the significance of TMDL assessments or any watershed study. We want to ensure that future TMDL assessments ...
Cytoscape: Network analysis and visualisation
Cytoscape: Network analysis and visualisation

... • Visual mapping of data to properties  allows for representation of multiple  dimensions of data • >10 visible properties of nodes (node  shape, size, colour, opacity, line attributes,  etc…) + more for edges • Examine different types of experimental  results or analysis simultaneously on a  networ ...
Data Mining
Data Mining

... and potatoes together, he or she is likely to also buy beef. Such information can be used as the basis for decisions about marketing activities such as, e.g., promotional pricing or . In addition to the above example from market basket analysis association rules are employed today in many applicatio ...
1) of
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PPT - NUS

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CUSTOMER_CODE SMUDE DIVISION_CODE SMUDE
CUSTOMER_CODE SMUDE DIVISION_CODE SMUDE

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for networks - Vanderbilt Kennedy Center
for networks - Vanderbilt Kennedy Center

... Genotype + Environment + DEVELOPMENT ==> Phenotype 1) Astounding Results Importance of Network thinking in development and physiology for data to explain phenotype (e.g. PAX6) ...
A Novel Method to Detect Identities in tRNA Genes Using Sequence
A Novel Method to Detect Identities in tRNA Genes Using Sequence

... We applied the method to Class I tRNAs to detect characteristic sites. We found that about 40% of characteristic sites that we detected are identities that have been detected experimentally, and that the remaining characteristic sites are in T and D domains which are the elbow regions of tRNAs. This ...
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MultipleSequenceAlignment
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... • Crops for the future will be based on advanced research and breeding using molecular methods • The genome sequencing and other ‘omics technologies are creating a data deluge • Distributed in centres around globe – particularly so for of agricultural species • Next data tsunami coming from image ba ...
Chapter 26 Presentation-Phylogeny and the Tree of Life
Chapter 26 Presentation-Phylogeny and the Tree of Life

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my_phylogeny1
my_phylogeny1

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ppt - r-evolution research server
ppt - r-evolution research server

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The present genetic tests

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Investigating Polar Bear and Giant Panda Ancestry
Investigating Polar Bear and Giant Panda Ancestry

... distance of 0.00 indicates identical sequences and as the difference in gene sequences increases so does the number). 2. Provide a phylogenetic tree of the bears and the panda. Label the lines on the tree with the corresponding distances. 3. Explain and provide support for the conclusions made by th ...
STRAW: Species TRee Analysis Web server | Nucleic Acids
STRAW: Species TRee Analysis Web server | Nucleic Acids

... MP-EST, STAR and NJst use gene trees estimated from DNA sequence data to infer species trees. Uncertainty of the estimated gene trees is incorporated in estimation of species trees using bootstrap techniques. In the MP-EST method, species trees are estimated from a collection of rooted gene trees by ...
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Quantitative comparative linguistics

Statistical methods have been used in comparative linguistics since at least the 1950s (see Swadesh list). Since about the year 2000, there has been a renewed interest in the topic, based on the application of methods of computational phylogenetics and cladistics to define an optimal tree (or network) to represent a hypothesis about the evolutionary ancestry and perhaps its language contacts. The probability of relatedness of languages can be quantified and sometimes the proto-languages can be approximately dated.The topic came the attention of the popular press in 2003 after the publication of a short study on Indo-European in Nature (Gray and Atkinson 2003). A volume of articles on Phylogenetic Methods and the Prehistory of Languages was published in 2006 as the result of a conference held in Cambridge in 2004.A goal of comparative historical linguistics is to identify instances of genetic relatedness amongst languages. The steps in quantitative analysis are (i) to devise a procedure based on theoretical grounds, on a particular model or on past experience, etc. (ii) to verify the procedure by applying it to some data where there exists a large body of linguistic opinion for comparison (this may lead to a revision of the procedure of stage (i) or at the extreme of its total abandonment) (iii) to apply the procedure to data where linguistic opinions have not yet been produced, have not yet been firmly established or perhaps are even in conflict.Applying phylogenetic methods to languages is a multi-stage process (a) the encoding stage - getting from real languages to some expression of the relationships between them in the form of numerical or state data, so that those data can then be used as input to phylogenetic methods (b) the representation stage - applying phylogenetic methods to extract from those numerical and/or state data a signal that is converted into some useful form of representation, usually two dimensional graphical ones such as trees or networks, which synthesise and ""collapse"" what are often highly complex multi dimensional relationships in the signal (c) the interpretation stage - assessing those tree and network representations to extract from them what they actually mean for real languages and their relationships through time.
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