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 final Hugo expected measured Rank
Results: HTML CSV LaTeX Showing element 1 to 50 of 3206 in total
description  :
final
Hugo
expected
measured
Rank
0.000219976 no value 0.7865 0.000173011 3206
C1orf166 2.59675 0.000571223 3205
0.036862138 CHMP2B 0.104721 0.00386024 3199
0.036862209 CHMP4B 0.85608 0.031557 3196
0.036862264 CHMP4C 0.649583 0.0239451 3194
0.037314982 FIBCD1 1.34852 0.05032 3191
0.04678744 CCDC104 1.01816 0.0476371 3185
0.049410892 PYCRL 1.32794 0.0656147 3184
0.055311655 C6orf130 0.333333 0.0184372 3176
NIPA2 3175
0.06471012 C5orf33 11.3823 0.73655 3167
0.065381433 MAGEB18 1.00804 0.0659071 3154
0.065381739 NSMCE4A 25.135 1.64337 3139
0.065381917 MAGEB10 1.01213 0.066175 3136
0.068499242 CC2D1A 1.29368 0.0886161 3129
0.088193051 C1orf14 0.634694 0.0559756 3119
0.097635809 METTL2A 0.498014 0.048624 3091
TM4SF19 3089
0.097635972 FAM20A 0.397415 0.038802 3087
0.103197055 C1orf156 0.353982 0.0365299 3070
0.103197093 no value 0.517345 0.0533885 3069
0.117651073 UBE2E2 1.62653 0.191363 3032
0.117651086 PTCD1 1.09557 0.128895 3031
0.121833673 FRY 0.266776 0.0325023 3013
0.125273906 SEPT11 1.08705 0.136179 3007
0.12785257 C1orf164 1.33704 0.170944 3002
0.135336712 HS3ST4 0.155504 0.0210454 2990
0.138195 C9orf68 1 0.138195 2987
0.139559153 MTERFD1 0.285269 0.0398119 2981
0.141551046 RIBC2 0.735452 0.104104 2970
0.146165148 FRMPD4 0.689453 0.100774 2959
0.152530807 SLC30A9 0.679961 0.103715 2945
0.157068631 VPS37B 0.682084 0.107134 2938
0.157207261 VPS37C 0.529029 0.0831672 2936
0.167353852 NUP93 0.704322 0.117871 2925
0.174141808 ANKS6 0.241467 0.0420495 2911
0.174142027 SAP30L 0.187331 0.0326222 2908
0.174142084 TMEM55A 0.332958 0.057982 2907
0.174142329 PLEKHG2 0.139564 0.024304 2905
0.175384941 LASS5 0.822334 0.144225 2893
0.178353445 SPTY2D1 0.285736 0.050962 2890
0.179909858 C9orf95 0.515188 0.0926874 2889
0.184481531 CXorf56 0.278146 0.0513128 2880
0.188897649 no value 0.196598 0.0371369 2872
0.188940403 ORAI2 0.163279 0.03085 2867
0.188941031 ORAI3 0.196899 0.0372023 2863
0.188941052 ORAI1 0.162737 0.0307477 2860
0.193516584 ZNF496 0.849984 0.164486 2824
0.193522393 ZNF449 0.852537 0.164985 2822
0.197047403 C9orf23 0.616542 0.121488 2812

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/