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