Scientific

MK5 Microarray Data


Affected Genes - Ontology Breakdown - Gene Enrichment - Proteome Analysis

These are the micro-array results of a differential gene expression microarray experiments and the subsequent analysis steps performed on them. The up/down- regulation ratio was obtained by measuring WT cells against MK5 activated cells. See material and methods for technical information as well as the data usage policy.

MK5 Proteome Network Type I Analysis

Type 1 network in which we propagated the absolute log regulation ratio abs(log(r/g)). We used the filtered lowest boundary of the confidence interval for the microarray measurement based and used the high confidence interaction map. Because type-I networks tend to favour highly connected proteins we tested a normalisation scheme in which we would run the network once with real values (the measured column) and once with simulated values where each measured point is set to 1 instead of the actual signal (the expected column). Afterwards we divided the measured value by the expected value. This normalisation scheme works to a certain extend but will lead to a variance that is directly related to the connectivity of each protein. In the end we dropped the use of Type-I networks due to the many technical problems they pose.


Navigation/Query Panel:
Click on the attribute name to hide/unhide it. The green arrows can be used to shift columns left/right. Exact word match is written as =..., regular expressions can be matched with ~.... To select all values larger or equal than use >.... This would be <... for values smaller or equal than. To select all values within a specific range use [...,...].
Gene description measured Rank expected final Hugo
Results: HTML CSV LaTeX Showing element 101 to 150 of 3206 in total
description  :
measured
Rank
expected
final
Hugo
0.0384502 1616 0.160453 0.239635283 MAEA
1617 RMND5A
0.0385127 823 0.147402 0.261276645 TANC1
0.0385624 1119 0.153758 0.250799308 GTDC1
0.0385694 741 0.145821 0.264498255 ZCCHC8
743 HSDL2
0.0386201 1192 0.155349 0.24860218 ATP13A4
0.038682 2125 0.169567 0.228122217 TCP11L1
0.038802 3087 0.397415 0.097635972 FAM20A
0.0389719 377 0.139616 0.279136345 CCDC12
0.0391646 963 0.152962 0.25604137 C6orf32
0.0393961 1325 0.160458 0.245522816 CHCHD4
0.0394844 456 0.143261 0.275611646 ZMAT2
0.0395402 814 0.151289 0.261355419 EXDL2
0.0396993 343 0.139829 0.283913208 C16orf57
0.0397949 424 0.143472 0.277370497 ARHGAP23
0.0398119 2981 0.285269 0.139559153 MTERFD1
0.0401118 1295 0.163123 0.245899107 BUD13
0.0401445 502 0.146476 0.274068789 CDV3
0.0403612 900 0.155595 0.259399081 TEX9
0.0410035 847 0.157329 0.260622644 no value
0.0411817 1156 0.164951 0.249660202 CYB5D2
0.0413585 1009 0.162467 0.254565543 C20orf72
0.0415188 644 0.154846 0.268129626 no value
0.0415385 1669 0.173966 0.238773668 DEPDC5
0.0417836 1311 0.170042 0.245725174 SERBP1
0.0420495 2911 0.241467 0.174141808 ANKS6
0.0424937 1219 0.171305 0.248058726 WDR55
0.042516 357 0.151058 0.281454805 no value
0.0425806 1045 0.168127 0.253264496 TMEM87A
0.0431799 543 0.15929 0.27107728 LRRC4C
0.0434449 2213 0.193087 0.225001683 LRRC48
0.0436424 672 0.163636 0.266704148 no value
0.0436706 290 0.144696 0.301809311 NXNL1
0.0436957 2522 0.203458 0.21476521 no value
0.0441578 862 0.169647 0.260292254 PYROXD1
0.0442559 1561 0.183485 0.241196283 ARRDC4
0.0445191 1147 0.177917 0.250223981 TMEM132E
0.044904 1700 0.188793 0.237847802 no value
0.0452858 1146 0.18098 0.250225439 TMEM132B
0.0461397 1799 0.196587 0.234703719 FAM57B
0.0465063 1145 0.185855 0.250228942 TMEM132D
0.0467541 1562 0.193844 0.241194466 ARRDC3
0.0476371 3185 1.01816 0.04678744 CCDC104
0.0476698 2123 0.208966 0.228122278 TCP11L2
0.0480412 516 0.176368 0.272391817 METT10D
0.0483186 356 0.171674 0.281455549 no value
0.048624 3089 0.498014 0.097635809 TM4SF19
3091 METTL2A
0.0488461 1642 0.204356 0.239024545 no value

Legend:
- Rank is the rank after comparing the two networks
- Gene is the ensembl human gene identifier measured by 1 or more probes on the microarray
- Hugo is the bloody hugo identifier as demanded by the BMC Bioinformatics idiots

- http://analysis.yellowcouch.org/