Freiburg RNA Tools
BrainDead - Results
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BrainDead 4526878

Input and runtime details for job 4526878 (precomputed example)

Training data

? Class-annotated RNAs in FASTA[.fa]

Model parameters

? k-mers of interest
AA,AGA,AGGU,AGU,AGUU,CU,GAA,GAGG,GG,GGG,GU,GUU,UGA,UGU,UU,UUG,UUGU,UUU
? k-mer features reflect
number of occurrences (feature is number >= 0)
? Max. energy ranked stable-3
? Machine learning model
Support Vector Classification using RBF kernel

Candidate data

? Candidate RNAs in FASTA[.fa]

Job ID 4526878 (server version trunk)

?Job Submitted & Queued@ Wed Feb 10 15:00:26 CET 2021
?BrainDead Started@ Wed Feb 10 15:16:53 CET 2021
?BrainDead Finished & Post-Processing@ Wed Feb 10 15:16:53 CET 2021
?Post-Processing Finished@ Wed Feb 10 15:17:07 CET 2021
?Job Completed@ Wed Feb 10 15:17:11 CET 2021
 DIRECT ACCESS: http://rna.informatik.uni-freiburg.de/RetrieveResults.jsp?jobID=4526878&toolName=BrainDead ( 30 days expiry )

Description of the job

miRNAs as ligands for microglia activation

This example summarizes our study that investigates the ability of mature miRNAs to act as immune receptor ligands. The ability of extracellular miRNAs to directly activate receptors is a recently discovered new field of operation of miRNAs beside their classic role in post-transcriptional gene regulation. The small RNAs available within the example's training data were experimentally tested for their potential to activate murine microglia cells in vitro. They are pre-classified as +/-1 when found activating or non-activating, resp., using fold change analyses based TNF-alpha concentration measurements. The example's training data set comprises both the original training data (top group) as well as the experimentally verified candidate sequences (middle and bottom group) from our initial BrainDead main publication (see list of references within Help page). For details on the selected k-mers, please refer to the manuscript. The candidate set covers all mature human miRNAs from mirBase v22.1.

? Output download complete results [zip]

Downloads

Predictions for candidate RNAs

Predicted class

Sort by selecting a column name.
RNA id class rank prob(1)
hsa-miR-205-5p -1.000 1201.000 0.368
hsa-miR-4727-5p -1.000 1202.000 0.368
hsa-miR-4733-3p -1.000 1203.000 0.367
hsa-miR-5004-3p -1.000 1204.000 0.366
hsa-miR-4645-5p -1.000 1205.000 0.365
hsa-miR-939-3p -1.000 1206.000 0.365
hsa-miR-3181 -1.000 1207.000 0.365
hsa-miR-4741 -1.000 1208.000 0.365
hsa-miR-3681-3p -1.000 1209.000 0.365
hsa-miR-6807-3p -1.000 1210.000 0.365
hsa-miR-7974 -1.000 1211.000 0.364
hsa-miR-588 -1.000 1212.000 0.364
hsa-miR-8052 -1.000 1213.000 0.364
hsa-miR-4684-3p -1.000 1214.000 0.364
hsa-miR-12127 -1.000 1215.000 0.363
hsa-miR-373-3p -1.000 1216.000 0.363
hsa-miR-4740-5p -1.000 1217.000 0.363
hsa-miR-5187-3p -1.000 1218.000 0.363
hsa-miR-6804-5p -1.000 1219.000 0.362
hsa-miR-192-5p -1.000 1220.000 0.361
hsa-miR-372-3p -1.000 1221.000 0.360
hsa-miR-1303 -1.000 1222.000 0.360
hsa-miR-6763-3p -1.000 1223.000 0.359
hsa-miR-6777-3p -1.000 1224.000 0.359
hsa-miR-6790-3p -1.000 1225.000 0.359
hsa-miR-6800-3p -1.000 1226.000 0.359
hsa-miR-1912-5p -1.000 1227.000 0.359
hsa-miR-450b-3p -1.000 1228.000 0.359
hsa-miR-663b -1.000 1229.000 0.358
hsa-miR-4653-5p -1.000 1230.000 0.357
hsa-miR-5188 -1.000 1231.000 0.356
hsa-miR-6753-3p -1.000 1232.000 0.356
hsa-miR-6744-3p -1.000 1233.000 0.356
hsa-miR-3124-3p -1.000 1234.000 0.356
hsa-miR-526b-5p -1.000 1235.000 0.355
hsa-miR-6806-5p -1.000 1236.000 0.355
hsa-miR-6776-5p -1.000 1237.000 0.354
hsa-miR-1249-5p -1.000 1238.000 0.354
hsa-miR-376a-2-5p -1.000 1239.000 0.354
hsa-miR-219b-3p -1.000 1240.000 0.353
hsa-miR-520d-3p -1.000 1241.000 0.352
hsa-miR-4296 -1.000 1242.000 0.352
hsa-miR-4659b-5p -1.000 1243.000 0.352
hsa-miR-188-5p -1.000 1244.000 0.352
hsa-miR-504-3p -1.000 1245.000 0.351
hsa-miR-645 -1.000 1246.000 0.351
hsa-miR-1269a -1.000 1247.000 0.351
hsa-miR-3651 -1.000 1248.000 0.351
hsa-miR-4691-5p -1.000 1249.000 0.351
hsa-miR-3675-5p -1.000 1250.000 0.350
hsa-miR-181a-5p -1.000 1251.000 0.350
hsa-miR-9983-3p -1.000 1252.000 0.349
hsa-miR-337-5p -1.000 1253.000 0.349
hsa-miR-629-5p -1.000 1254.000 0.349
hsa-miR-5586-3p -1.000 1255.000 0.347
hsa-miR-4781-3p -1.000 1256.000 0.347
hsa-miR-4717-3p -1.000 1257.000 0.347
hsa-miR-4671-3p -1.000 1258.000 0.347
hsa-miR-4804-3p -1.000 1259.000 0.346
hsa-miR-4670-3p -1.000 1260.000 0.345
hsa-miR-6842-3p -1.000 1261.000 0.345
hsa-miR-503-5p -1.000 1262.000 0.345
hsa-miR-526b-3p -1.000 1263.000 0.345
hsa-miR-380-3p -1.000 1264.000 0.344
hsa-miR-8067 -1.000 1265.000 0.344
hsa-miR-4730 -1.000 1266.000 0.344
hsa-miR-4693-5p -1.000 1267.000 0.343
hsa-miR-3650 -1.000 1268.000 0.342
hsa-miR-4256 -1.000 1269.000 0.342
hsa-miR-548ac -1.000 1270.000 0.342
hsa-miR-4772-3p -1.000 1271.000 0.342
hsa-miR-532-3p -1.000 1272.000 0.342
hsa-miR-5581-3p -1.000 1273.000 0.341
hsa-miR-548u -1.000 1274.000 0.341
hsa-miR-3670 -1.000 1275.000 0.341
hsa-miR-4316 -1.000 1276.000 0.341
hsa-miR-4320 -1.000 1277.000 0.341
hsa-miR-371a-5p -1.000 1278.000 0.341
hsa-miR-3186-3p -1.000 1279.000 0.340
hsa-miR-12126 -1.000 1280.000 0.339
hsa-miR-216b-3p -1.000 1281.000 0.338
hsa-miR-3180-5p -1.000 1282.000 0.338
hsa-miR-7108-5p -1.000 1283.000 0.338
hsa-miR-4254 -1.000 1284.000 0.337
hsa-miR-6862-3p -1.000 1285.000 0.337
hsa-miR-10392-3p -1.000 1286.000 0.337
hsa-miR-3085-3p -1.000 1287.000 0.337
hsa-miR-3606-5p -1.000 1288.000 0.337
hsa-miR-5094 -1.000 1289.000 0.337
hsa-miR-708-3p -1.000 1290.000 0.336
hsa-miR-3615 -1.000 1291.000 0.335
hsa-miR-6741-3p -1.000 1292.000 0.335
hsa-miR-6861-3p -1.000 1293.000 0.335
hsa-miR-624-3p -1.000 1294.000 0.334
hsa-miR-612 -1.000 1295.000 0.334
hsa-miR-4471 -1.000 1296.000 0.333
hsa-miR-5692b -1.000 1297.000 0.333
hsa-miR-1207-3p -1.000 1298.000 0.333
hsa-miR-4799-3p -1.000 1299.000 0.333
hsa-miR-3934-5p -1.000 1300.000 0.333
Rows: 1-100 101-200 201-300 301-400 401-500 501-600 601-700 701-800 801-900 901-1000 1001-1100 1101-1200 1201-1300 1301-1400 1401-1500 1501-1600 1601-1700 1701-1800 1801-1900 1901-2000 2001-2100 2101-2200 2201-2300 2301-2400 2401-2500 2501-2600 2601-2656 all

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When using BrainDead please cite :

Results are computed with BrainDead version 1.0.1 using IntaRNA 3.1.5 and Vienna RNA package 2.4.14