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