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-889-5p -1.000 1901.000 0.173
hsa-miR-4797-3p -1.000 1902.000 0.173
hsa-miR-6502-3p -1.000 1903.000 0.173
hsa-miR-5189-5p -1.000 1904.000 0.173
hsa-miR-200b-3p -1.000 1905.000 0.173
hsa-miR-8087 -1.000 1906.000 0.172
hsa-miR-6503-5p -1.000 1907.000 0.172
hsa-miR-4791 -1.000 1908.000 0.172
hsa-miR-7704 -1.000 1909.000 0.172
hsa-miR-1204 -1.000 1910.000 0.171
hsa-miR-1197 -1.000 1911.000 0.171
hsa-miR-572 -1.000 1912.000 0.171
hsa-miR-3619-5p -1.000 1913.000 0.171
hsa-miR-4479 -1.000 1914.000 0.171
hsa-miR-3654 -1.000 1915.000 0.171
hsa-miR-200b-5p -1.000 1916.000 0.171
hsa-miR-4327 -1.000 1917.000 0.171
hsa-miR-3667-5p -1.000 1918.000 0.171
hsa-miR-6715b-3p -1.000 1919.000 0.171
hsa-miR-5006-5p -1.000 1920.000 0.171
hsa-miR-1289 -1.000 1921.000 0.170
hsa-miR-6875-5p -1.000 1922.000 0.170
hsa-miR-1973 -1.000 1923.000 0.170
hsa-miR-519c-5p -1.000 1924.000 0.170
hsa-miR-519b-5p -1.000 1925.000 0.170
hsa-miR-523-5p -1.000 1926.000 0.170
hsa-miR-518f-5p -1.000 1927.000 0.170
hsa-miR-518e-5p -1.000 1928.000 0.170
hsa-miR-522-5p -1.000 1929.000 0.170
hsa-miR-519a-5p -1.000 1930.000 0.170
hsa-miR-3120-3p -1.000 1931.000 0.170
hsa-miR-4446-3p -1.000 1932.000 0.170
hsa-miR-4745-5p -1.000 1933.000 0.170
hsa-miR-520f-5p -1.000 1934.000 0.169
hsa-miR-3136-5p -1.000 1935.000 0.169
hsa-miR-655-5p -1.000 1936.000 0.169
hsa-miR-7158-5p -1.000 1937.000 0.169
hsa-miR-6728-5p -1.000 1938.000 0.168
hsa-miR-4749-5p -1.000 1939.000 0.168
hsa-miR-4774-3p -1.000 1940.000 0.168
hsa-miR-10393-3p -1.000 1941.000 0.168
hsa-miR-376b-3p -1.000 1942.000 0.167
hsa-miR-4647 -1.000 1943.000 0.167
hsa-miR-6891-5p -1.000 1944.000 0.167
hsa-miR-6741-5p -1.000 1945.000 0.167
hsa-miR-4726-5p -1.000 1946.000 0.167
hsa-miR-938 -1.000 1947.000 0.167
hsa-miR-4534 -1.000 1948.000 0.167
hsa-miR-410-3p -1.000 1949.000 0.167
hsa-miR-1288-5p -1.000 1950.000 0.167
hsa-miR-7109-5p -1.000 1951.000 0.167
hsa-miR-7-2-3p -1.000 1952.000 0.166
hsa-miR-633 -1.000 1953.000 0.166
hsa-miR-3184-3p -1.000 1954.000 0.166
hsa-miR-3691-3p -1.000 1955.000 0.166
hsa-miR-374c-5p -1.000 1956.000 0.166
hsa-miR-5588-3p -1.000 1957.000 0.166
hsa-miR-1185-2-3p -1.000 1958.000 0.166
hsa-miR-217-5p -1.000 1959.000 0.165
hsa-miR-6785-5p -1.000 1960.000 0.165
hsa-miR-4319 -1.000 1961.000 0.165
hsa-miR-7162-3p -1.000 1962.000 0.165
hsa-miR-4527 -1.000 1963.000 0.165
hsa-miR-3614-5p -1.000 1964.000 0.164
hsa-miR-1225-5p -1.000 1965.000 0.164
hsa-miR-1307-3p -1.000 1966.000 0.164
hsa-miR-215-5p -1.000 1967.000 0.163
hsa-miR-6819-5p -1.000 1968.000 0.163
hsa-miR-3618 -1.000 1969.000 0.163
hsa-miR-12132 -1.000 1970.000 0.163
hsa-miR-212-3p -1.000 1971.000 0.163
hsa-miR-4665-3p -1.000 1972.000 0.163
hsa-miR-6861-5p -1.000 1973.000 0.163
hsa-miR-4291 -1.000 1974.000 0.163
hsa-miR-4802-3p -1.000 1975.000 0.163
hsa-miR-7112-5p -1.000 1976.000 0.163
hsa-miR-135a-3p -1.000 1977.000 0.162
hsa-miR-3916 -1.000 1978.000 0.162
hsa-miR-4499 -1.000 1979.000 0.162
hsa-miR-576-3p -1.000 1980.000 0.161
hsa-miR-4766-3p -1.000 1981.000 0.161
hsa-miR-1912-3p -1.000 1982.000 0.161
hsa-miR-4489 -1.000 1983.000 0.161
hsa-miR-6132 -1.000 1984.000 0.160
hsa-miR-4539 -1.000 1985.000 0.160
hsa-miR-3158-3p -1.000 1986.000 0.160
hsa-miR-6763-5p -1.000 1987.000 0.160
hsa-miR-3128 -1.000 1988.000 0.159
hsa-miR-6864-5p -1.000 1989.000 0.159
hsa-miR-4785 -1.000 1990.000 0.159
hsa-miR-2861 -1.000 1991.000 0.159
hsa-miR-491-5p -1.000 1992.000 0.159
hsa-miR-195-5p -1.000 1993.000 0.158
hsa-miR-198 -1.000 1994.000 0.158
hsa-miR-4298 -1.000 1995.000 0.157
hsa-miR-6771-5p -1.000 1996.000 0.157
hsa-miR-664b-5p -1.000 1997.000 0.157
hsa-miR-3714 -1.000 1998.000 0.157
hsa-miR-7706 -1.000 1999.000 0.157
hsa-miR-187-5p -1.000 2000.000 0.157
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