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-543 -1.000 2401.000 0.083
hsa-miR-323b-3p -1.000 2402.000 0.083
hsa-miR-3913-3p -1.000 2403.000 0.083
hsa-miR-5581-5p -1.000 2404.000 0.082
hsa-miR-4536-5p -1.000 2405.000 0.082
hsa-miR-3658 -1.000 2406.000 0.082
hsa-miR-6510-5p -1.000 2407.000 0.081
hsa-miR-6777-5p -1.000 2408.000 0.081
hsa-miR-3130-3p -1.000 2409.000 0.081
hsa-miR-128-3p -1.000 2410.000 0.081
hsa-miR-3126-5p -1.000 2411.000 0.081
hsa-miR-920 -1.000 2412.000 0.081
hsa-miR-183-3p -1.000 2413.000 0.080
hsa-miR-3173-3p -1.000 2414.000 0.080
hsa-miR-6124 -1.000 2415.000 0.080
hsa-miR-7111-5p -1.000 2416.000 0.080
hsa-miR-627-5p -1.000 2417.000 0.080
hsa-miR-3976 -1.000 2418.000 0.080
hsa-miR-10522-5p -1.000 2419.000 0.079
hsa-miR-6750-3p -1.000 2420.000 0.079
hsa-miR-5585-5p -1.000 2421.000 0.079
hsa-miR-3610 -1.000 2422.000 0.079
hsa-miR-8059 -1.000 2423.000 0.078
hsa-miR-6735-5p -1.000 2424.000 0.077
hsa-miR-6888-5p -1.000 2425.000 0.077
hsa-miR-4468 -1.000 2426.000 0.076
hsa-miR-6743-5p -1.000 2427.000 0.076
hsa-miR-485-5p -1.000 2428.000 0.075
hsa-miR-6817-5p -1.000 2429.000 0.075
hsa-miR-6788-5p -1.000 2430.000 0.075
hsa-miR-4531 -1.000 2431.000 0.075
hsa-miR-452-3p -1.000 2432.000 0.075
hsa-miR-5010-5p -1.000 2433.000 0.075
hsa-miR-3179 -1.000 2434.000 0.075
hsa-miR-523-3p -1.000 2435.000 0.074
hsa-miR-125b-2-3p -1.000 2436.000 0.074
hsa-miR-454-3p -1.000 2437.000 0.074
hsa-miR-4485-3p -1.000 2438.000 0.074
hsa-miR-142-5p -1.000 2439.000 0.074
hsa-miR-3190-3p -1.000 2440.000 0.074
hsa-miR-6508-5p -1.000 2441.000 0.074
hsa-miR-6828-5p -1.000 2442.000 0.074
hsa-miR-12122 -1.000 2443.000 0.074
hsa-miR-10401-5p -1.000 2444.000 0.074
hsa-miR-6840-5p -1.000 2445.000 0.074
hsa-miR-2110 -1.000 2446.000 0.073
hsa-miR-654-5p -1.000 2447.000 0.073
hsa-miR-302b-5p -1.000 2448.000 0.073
hsa-miR-6838-5p -1.000 2449.000 0.073
hsa-miR-3121-3p -1.000 2450.000 0.073
hsa-miR-4796-3p -1.000 2451.000 0.073
hsa-miR-8060 -1.000 2452.000 0.073
hsa-miR-4638-5p -1.000 2453.000 0.073
hsa-miR-370-3p -1.000 2454.000 0.073
hsa-miR-216a-3p -1.000 2455.000 0.072
hsa-miR-765 -1.000 2456.000 0.072
hsa-miR-137-3p -1.000 2457.000 0.072
hsa-miR-486-3p -1.000 2458.000 0.072
hsa-miR-1202 -1.000 2459.000 0.072
hsa-miR-4519 -1.000 2460.000 0.072
hsa-miR-3155b -1.000 2461.000 0.072
hsa-miR-4294 -1.000 2462.000 0.072
hsa-miR-5003-5p -1.000 2463.000 0.072
hsa-miR-3162-5p -1.000 2464.000 0.072
hsa-miR-550a-5p -1.000 2465.000 0.072
hsa-miR-6826-5p -1.000 2466.000 0.072
hsa-miR-4706 -1.000 2467.000 0.072
hsa-miR-3914 -1.000 2468.000 0.072
hsa-miR-874-5p -1.000 2469.000 0.072
hsa-miR-4747-5p -1.000 2470.000 0.072
hsa-miR-5579-3p -1.000 2471.000 0.071
hsa-miR-4698 -1.000 2472.000 0.071
hsa-miR-10395-5p -1.000 2473.000 0.071
hsa-miR-6758-5p -1.000 2474.000 0.071
hsa-miR-3197 -1.000 2475.000 0.071
hsa-miR-6892-5p -1.000 2476.000 0.071
hsa-miR-520b-5p -1.000 2477.000 0.071
hsa-miR-519a-2-5p -1.000 2478.000 0.071
hsa-miR-4487 -1.000 2479.000 0.070
hsa-miR-6881-5p -1.000 2480.000 0.070
hsa-miR-7845-5p -1.000 2481.000 0.070
hsa-miR-6126 -1.000 2482.000 0.070
hsa-miR-7-1-3p -1.000 2483.000 0.070
hsa-miR-1237-5p -1.000 2484.000 0.070
hsa-miR-550a-3-5p -1.000 2485.000 0.070
hsa-miR-1268b -1.000 2486.000 0.069
hsa-miR-4442 -1.000 2487.000 0.069
hsa-miR-4728-5p -1.000 2488.000 0.069
hsa-miR-761 -1.000 2489.000 0.068
hsa-miR-6760-5p -1.000 2490.000 0.068
hsa-miR-3926 -1.000 2491.000 0.068
hsa-miR-500a-3p -1.000 2492.000 0.068
hsa-miR-501-3p -1.000 2493.000 0.068
hsa-miR-31-5p -1.000 2494.000 0.067
hsa-miR-1295b-5p -1.000 2495.000 0.067
hsa-miR-3201 -1.000 2496.000 0.067
hsa-miR-6088 -1.000 2497.000 0.067
hsa-miR-7156-3p -1.000 2498.000 0.067
hsa-miR-4779 -1.000 2499.000 0.067
hsa-miR-1468-3p -1.000 2500.000 0.067
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