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-5699-5p -1.000 2501.000 0.067
hsa-miR-4502 -1.000 2502.000 0.067
hsa-miR-6767-5p -1.000 2503.000 0.066
hsa-miR-6807-5p -1.000 2504.000 0.066
hsa-miR-4667-5p -1.000 2505.000 0.066
hsa-miR-5584-5p -1.000 2506.000 0.066
hsa-miR-4769-5p -1.000 2507.000 0.066
hsa-miR-6131 -1.000 2508.000 0.066
hsa-miR-6125 -1.000 2509.000 0.065
hsa-miR-555 -1.000 2510.000 0.065
hsa-miR-130b-3p -1.000 2511.000 0.065
hsa-miR-8084 -1.000 2512.000 0.065
hsa-miR-3124-5p -1.000 2513.000 0.065
hsa-miR-6782-5p -1.000 2514.000 0.064
hsa-miR-4797-5p -1.000 2515.000 0.064
hsa-miR-202-3p -1.000 2516.000 0.064
hsa-miR-1236-5p -1.000 2517.000 0.064
hsa-miR-6890-5p -1.000 2518.000 0.063
hsa-miR-4724-5p -1.000 2519.000 0.063
hsa-miR-6878-5p -1.000 2520.000 0.062
hsa-miR-9-3p -1.000 2521.000 0.062
hsa-miR-3157-3p -1.000 2522.000 0.062
hsa-miR-483-5p -1.000 2523.000 0.062
hsa-miR-6873-5p -1.000 2524.000 0.062
hsa-miR-4484 -1.000 2525.000 0.062
hsa-miR-6505-5p -1.000 2526.000 0.062
hsa-miR-936 -1.000 2527.000 0.062
hsa-miR-6769b-5p -1.000 2528.000 0.062
hsa-miR-6508-3p -1.000 2529.000 0.061
hsa-miR-6882-5p -1.000 2530.000 0.061
hsa-miR-4314 -1.000 2531.000 0.061
hsa-miR-4732-5p -1.000 2532.000 0.061
hsa-miR-4660 -1.000 2533.000 0.061
hsa-miR-3910 -1.000 2534.000 0.061
hsa-miR-34a-3p -1.000 2535.000 0.061
hsa-miR-4799-5p -1.000 2536.000 0.061
hsa-miR-26a-5p -1.000 2537.000 0.060
hsa-miR-3662 -1.000 2538.000 0.060
hsa-miR-197-5p -1.000 2539.000 0.060
hsa-miR-9500 -1.000 2540.000 0.060
hsa-miR-378a-3p -1.000 2541.000 0.060
hsa-miR-378d -1.000 2542.000 0.060
hsa-miR-378c -1.000 2543.000 0.060
hsa-miR-4426 -1.000 2544.000 0.060
hsa-miR-3690 -1.000 2545.000 0.060
hsa-miR-4733-5p -1.000 2546.000 0.060
hsa-miR-551b-5p -1.000 2547.000 0.060
hsa-miR-3160-3p -1.000 2548.000 0.060
hsa-miR-6809-5p -1.000 2549.000 0.060
hsa-miR-6747-5p -1.000 2550.000 0.060
hsa-miR-6833-5p -1.000 2551.000 0.060
hsa-miR-6867-5p -1.000 2552.000 0.060
hsa-miR-711 -1.000 2553.000 0.059
hsa-miR-4261 -1.000 2554.000 0.059
hsa-miR-4271 -1.000 2555.000 0.059
hsa-miR-6879-5p -1.000 2556.000 0.059
hsa-miR-12136 -1.000 2557.000 0.059
hsa-miR-300 -1.000 2558.000 0.059
hsa-miR-191-5p -1.000 2559.000 0.058
hsa-miR-5591-5p -1.000 2560.000 0.058
hsa-miR-376c-3p -1.000 2561.000 0.058
hsa-miR-4306 -1.000 2562.000 0.058
hsa-miR-4434 -1.000 2563.000 0.058
hsa-miR-4436a -1.000 2564.000 0.058
hsa-miR-6895-5p -1.000 2565.000 0.058
hsa-miR-2115-3p -1.000 2566.000 0.057
hsa-miR-5191 -1.000 2567.000 0.057
hsa-miR-877-5p -1.000 2568.000 0.057
hsa-miR-492 -1.000 2569.000 0.057
hsa-miR-2116-3p -1.000 2570.000 0.057
hsa-miR-5695 -1.000 2571.000 0.057
hsa-miR-1247-3p -1.000 2572.000 0.057
hsa-miR-8063 -1.000 2573.000 0.056
hsa-miR-4438 -1.000 2574.000 0.056
hsa-miR-509-3-5p -1.000 2575.000 0.056
hsa-miR-4427 -1.000 2576.000 0.056
hsa-miR-5197-3p -1.000 2577.000 0.056
hsa-miR-4768-3p -1.000 2578.000 0.056
hsa-miR-628-3p -1.000 2579.000 0.056
hsa-miR-6501-3p -1.000 2580.000 0.056
hsa-miR-132-3p -1.000 2581.000 0.055
hsa-miR-3671 -1.000 2582.000 0.055
hsa-miR-6780b-5p -1.000 2583.000 0.055
hsa-miR-5189-3p -1.000 2584.000 0.054
hsa-miR-6717-5p -1.000 2585.000 0.054
hsa-miR-211-3p -1.000 2586.000 0.054
hsa-miR-4755-3p -1.000 2587.000 0.053
hsa-miR-6511b-5p -1.000 2588.000 0.053
hsa-miR-3144-5p -1.000 2589.000 0.053
hsa-miR-3133 -1.000 2590.000 0.053
hsa-miR-12124 -1.000 2591.000 0.052
hsa-miR-184 -1.000 2592.000 0.052
hsa-miR-604 -1.000 2593.000 0.051
hsa-miR-6801-5p -1.000 2594.000 0.050
hsa-miR-6859-5p -1.000 2595.000 0.050
hsa-miR-4436b-3p -1.000 2596.000 0.050
hsa-miR-6739-5p -1.000 2597.000 0.050
hsa-miR-620 -1.000 2598.000 0.050
hsa-miR-4445-3p -1.000 2599.000 0.050
hsa-miR-4644 -1.000 2600.000 0.050
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