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

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/