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: https://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-1323 -1.000 1101.000 0.404
hsa-miR-3911 -1.000 1102.000 0.404
hsa-miR-4761-5p -1.000 1103.000 0.403
hsa-miR-3943 -1.000 1104.000 0.402
hsa-miR-6070 -1.000 1105.000 0.402
hsa-miR-10a-5p -1.000 1106.000 0.401
hsa-miR-10b-5p -1.000 1107.000 0.401
hsa-miR-4268 -1.000 1108.000 0.400
hsa-miR-1182 -1.000 1109.000 0.400
hsa-miR-3920 -1.000 1110.000 0.399
hsa-miR-6505-3p -1.000 1111.000 0.399
hsa-miR-4279 -1.000 1112.000 0.399
hsa-miR-4685-3p -1.000 1113.000 0.399
hsa-miR-5690 -1.000 1114.000 0.399
hsa-miR-6876-5p -1.000 1115.000 0.398
hsa-miR-4699-5p -1.000 1116.000 0.398
hsa-miR-3170 -1.000 1117.000 0.398
hsa-miR-665 -1.000 1118.000 0.398
hsa-miR-4687-3p -1.000 1119.000 0.397
hsa-miR-423-5p -1.000 1120.000 0.396
hsa-miR-658 -1.000 1121.000 0.395
hsa-miR-376a-5p -1.000 1122.000 0.394
hsa-miR-7856-5p -1.000 1123.000 0.394
hsa-miR-4538 -1.000 1124.000 0.394
hsa-miR-4709-5p -1.000 1125.000 0.393
hsa-miR-3154 -1.000 1126.000 0.393
hsa-miR-6768-3p -1.000 1127.000 0.393
hsa-miR-6730-5p -1.000 1128.000 0.393
hsa-miR-12133 -1.000 1129.000 0.392
hsa-miR-8069 -1.000 1130.000 0.392
hsa-miR-301a-3p -1.000 1131.000 0.391
hsa-miR-219b-5p -1.000 1132.000 0.391
hsa-miR-4756-5p -1.000 1133.000 0.391
hsa-miR-4437 -1.000 1134.000 0.391
hsa-miR-1245b-5p -1.000 1135.000 0.391
hsa-miR-181c-5p -1.000 1136.000 0.390
hsa-let-7f-1-3p -1.000 1137.000 0.390
hsa-miR-548ax -1.000 1138.000 0.389
hsa-miR-3616-3p -1.000 1139.000 0.389
hsa-miR-1471 -1.000 1140.000 0.389
hsa-miR-3139 -1.000 1141.000 0.388
hsa-miR-4509 -1.000 1142.000 0.388
hsa-miR-345-5p -1.000 1143.000 0.387
hsa-miR-145-3p -1.000 1144.000 0.387
hsa-miR-3085-5p -1.000 1145.000 0.387
hsa-miR-1234-3p -1.000 1146.000 0.386
hsa-miR-8064 -1.000 1147.000 0.386
hsa-miR-520e-3p -1.000 1148.000 0.386
hsa-miR-326 -1.000 1149.000 0.385
hsa-miR-195-3p -1.000 1150.000 0.385
hsa-miR-302a-5p -1.000 1151.000 0.385
hsa-miR-4705 -1.000 1152.000 0.385
hsa-miR-1224-5p -1.000 1153.000 0.385
hsa-miR-4721 -1.000 1154.000 0.385
hsa-miR-374a-5p -1.000 1155.000 0.384
hsa-miR-127-3p -1.000 1156.000 0.384
hsa-miR-5194 -1.000 1157.000 0.384
hsa-miR-3940-5p -1.000 1158.000 0.383
hsa-miR-525-5p -1.000 1159.000 0.382
hsa-miR-6831-5p -1.000 1160.000 0.382
hsa-miR-1287-5p -1.000 1161.000 0.382
hsa-miR-4455 -1.000 1162.000 0.382
hsa-miR-10392-5p -1.000 1163.000 0.382
hsa-miR-4771 -1.000 1164.000 0.381
hsa-miR-671-3p -1.000 1165.000 0.380
hsa-miR-3622a-5p -1.000 1166.000 0.380
hsa-miR-19a-3p -1.000 1167.000 0.380
hsa-miR-19b-3p -1.000 1168.000 0.380
hsa-miR-298 -1.000 1169.000 0.379
hsa-miR-5008-5p -1.000 1170.000 0.379
hsa-miR-487a-3p -1.000 1171.000 0.379
hsa-miR-6721-5p -1.000 1172.000 0.379
hsa-miR-4478 -1.000 1173.000 0.378
hsa-miR-554 -1.000 1174.000 0.378
hsa-miR-378h -1.000 1175.000 0.378
hsa-miR-4507 -1.000 1176.000 0.378
hsa-miR-222-5p -1.000 1177.000 0.377
hsa-miR-4424 -1.000 1178.000 0.377
hsa-miR-7843-5p -1.000 1179.000 0.377
hsa-miR-190b-5p -1.000 1180.000 0.377
hsa-miR-939-5p -1.000 1181.000 0.377
hsa-miR-4708-3p -1.000 1182.000 0.376
hsa-let-7i-3p -1.000 1183.000 0.376
hsa-miR-4639-5p -1.000 1184.000 0.376
hsa-miR-4709-3p -1.000 1185.000 0.375
hsa-miR-498-5p -1.000 1186.000 0.374
hsa-miR-4759 -1.000 1187.000 0.374
hsa-miR-4524b-3p -1.000 1188.000 0.374
hsa-miR-328-3p -1.000 1189.000 0.373
hsa-miR-412-3p -1.000 1190.000 0.373
hsa-miR-380-5p -1.000 1191.000 0.373
hsa-miR-148a-3p -1.000 1192.000 0.372
hsa-miR-4480 -1.000 1193.000 0.371
hsa-miR-93-3p -1.000 1194.000 0.371
hsa-miR-6805-5p -1.000 1195.000 0.370
hsa-miR-483-3p -1.000 1196.000 0.369
hsa-miR-1237-3p -1.000 1197.000 0.369
hsa-miR-4436b-5p -1.000 1198.000 0.369
hsa-miR-607 -1.000 1199.000 0.369
hsa-miR-4700-3p -1.000 1200.000 0.369
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