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

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/