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

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/