User: teabonng

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teabonng20
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Posts by teabonng

<prev • 27 results • page 1 of 3 • next >
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Construction of coexpression networks from multiple datasets
... Hi Everyone, I plan to construct coexpression networks to find modules using various independent datasets from databases such as GEO. Would it be valid that for each dataset, I calculate the fold changes of all genes with respect to untreated samples. Then I combine all the multiple datasets to cal ...
coexpression networks coexpression written 15 days ago by teabonng20
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Node degree-weighted graph
... Hi everyone, I would like to ask for suggestions as how to convert a weighted graph from an unweighted graph, with the weights based on the degrees of nodes in the edges. Also, if there is a good python package for this that can handle thousands of nodes. Thank you very much! ...
network biology written 7 weeks ago by teabonng20
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ChIP-Seq tag counts
... Hi Everyone, Can I use tag counts from ChIP-Seq data as inputs for machine learning? I did not call peaks, however, so that the features will not be simply binary. Thank you for your help. teabonng ...
chip-seq machine learning written 7 months ago by teabonng20 • updated 7 months ago by WouterDeCoster41k
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Histone modification patterns
... Hi Everyone, Can anyone refer me to a good reference that shows evidence that genes that belong to the same regulatory pathway have similar histone modification patterns that can be statistically analyzed? Thank you. ...
chromatin pattern written 8 months ago by teabonng20
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PPI networks in disease vs. healthy
... Hi Everyone, I was reading about some PPIs recently. Please excuse if my question is too simple. My question is, if i reconstruct PPIs from healthy and diseased individuals from omics data, would you expect that the reconstructed PPIs will be different, even if only a few nodes? ...
ppi networks written 8 months ago by teabonng20 • updated 8 months ago by Kevin Blighe48k
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Comment: C: Machine learning predictor has no correlation with output variable
... Hi Jean-Karim, Thank you for your help. I would just like to further clarify, since the logistic regression takes into account the individual contributions of each feature, but I did not add any interaction terms. In this case, I'm not sure if i can say that there is some interaction among the fea ...
written 10 months ago by teabonng20
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Machine learning predictor has no correlation with output variable
... Hi Everyone, I built a logistic regression classifier for predicting genes that has around 75% accuracy. Predictor A is a transcription factor that is a top predictor. However, when I look at the the scatterplot there is absolutely no correlation and the positive and negative examples show the same ...
machine learning written 10 months ago by teabonng20 • updated 10 months ago by Jean-Karim Heriche20k
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Comment: C: Neural networks feature importance
... Hi karl.stamm, Can you provide an example on how to adapt Garson's algorithm for multiple neurons? Can I calculate the importances with respect to each neuron instead? Thanks ...
written 11 months ago by teabonng20
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Neural networks feature importance
... Hi everyone, I am using a neural network with two output neurons for my omics data to predict the binary classification of genes. It is important in the study to know the feature importance. I know that the Garson's algorithm and connection weights algorithm are used in neural networks with one hid ...
neural network written 11 months ago by teabonng20 • updated 11 months ago by karl.stamm3.5k
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Comment: C: Data Transformations for machine learning
... Hi Kevin, Thanks for your reply. I have decided to log transform all the features. Then do the standardization so that they have more or less the same range. Then use as input for the neural network. Would this make sense? Thanks, teabonng ...
written 12 months ago by teabonng20

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Popular Question 5 weeks ago, created a question with more than 1,000 views. For edgeR - normalized counts from multiple datasets
Popular Question 5 months ago, created a question with more than 1,000 views. For edger model matrix design of linear model

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