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