evaluatePrediction()
: This bug makes the function always take the first level as positive label, yielding wrong values for some metrics (such as sensitivity, specificity, etc) when the first level is negative. This issue made no effect on the results reported in LION's paper. run_confidentPrediction()
to get prediction results of multiple methods in one run.run_LncADeep()
for prediction using LncADeep's feature set.computeMLC()
to compute the most-like CDS (MLC) region.EDP
which supports applying entropy density profile to sequence intrinsic features.evaluatePrediction()
for prediction evaluation."retrain"
and "feature"
modes are added to function run_LION()
, run_RPISeq()
, run_lncPro()
and run_rpiCOOL()
. Now users can use ready-to-use functions to extract features or retrain the models of LION, RPISeq, lncPro and rpiCOOL.Add the following code to your website.
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