KSV58758.1 protein (Acetivibrio ethanolgignens)

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Known Interactions

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Predicted Interactions

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Score

KSV58758.1

Hypothetical protein; Derived by automated computational analysis using gene prediction method: GeneMarkS+. (311 aa)

Predicted Functional Partners:

KSV58759.1

0.427

KSV58757.1

0.425

Your Current Organism:

Acetivibrio ethanolgignens

NCBI taxonomy Id: 290052
Other names: A. ethanolgignens, ATCC 33324, Acetivibrio ethanoligignens, DSM 3005, LMG 7055, LMG:7055, strain 77-6

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Browse interactions in tabular form:

node1	node2	node1 accession	node2 accession	node1 annotation	node2 annotation	score
KSV58757.1	KSV58758.1	ASU35_11885	ASU35_11890	Hypothetical protein; Derived by automated computational analysis using gene prediction method: GeneMarkS+.	Hypothetical protein; Derived by automated computational analysis using gene prediction method: GeneMarkS+.	0.425
KSV58758.1	KSV58757.1	ASU35_11890	ASU35_11885	Hypothetical protein; Derived by automated computational analysis using gene prediction method: GeneMarkS+.	Hypothetical protein; Derived by automated computational analysis using gene prediction method: GeneMarkS+.	0.425
KSV58758.1	KSV58759.1	ASU35_11890	ASU35_11895	Hypothetical protein; Derived by automated computational analysis using gene prediction method: GeneMarkS+.	Hypothetical protein; Derived by automated computational analysis using gene prediction method: GeneMarkS+.	0.427
KSV58759.1	KSV58758.1	ASU35_11895	ASU35_11890	Hypothetical protein; Derived by automated computational analysis using gene prediction method: GeneMarkS+.	Hypothetical protein; Derived by automated computational analysis using gene prediction method: GeneMarkS+.	0.427

Network Stats

number of nodes:

3

number of edges:

2

average node degree:

1.33

avg. local clustering coefficient:

0.667

expected number of edges:

2

PPI enrichment p-value:

0.527

your network does not have significantly more
interactions than expected (what does that mean?)

Functional enrichments in your networkNote: some enrichments may be expected here (why?)
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Biological Process (Gene Ontology)

GO-term

description

count in network

strength

signal

false discovery rate

GO:0006641

Triglyceride metabolic process

5 of 17

2.65

4.41

4.08e-09

GO:0046486

Glycerolipid metabolic process

7 of 152

1.85

3.36

4.08e-09

GO:0044255

Cellular lipid metabolic process

9 of 558

1.39

2.21

4.08e-09

GO:0090407

Organophosphate biosynthetic process

6 of 321

1.45

1.77

1.04e-05

GO:0046167

glycerol-3-phosphate biosynthetic process

2 of 2

3.18

1.77

0.00063

(more ...)

Molecular Function (Gene Ontology)

GO-term

description

count in network

strength

signal

false discovery rate

GO:0003841

1-acylglycerol-3-phosphate O-acyltransferase activity

3 of 4

3.06

2.78

8.68e-06

GO:0008374

O-acyltransferase activity

4 of 31

2.29

2.61

8.68e-06

GO:0004370

Glycerol kinase activity

2 of 2

3.18

1.76

0.00066

GO:0008195

Phosphatidate phosphatase activity

2 of 5

2.79

1.55

0.0015

GO:0016740

Transferase activity

6 of 1392

0.82

0.52

0.0177

(more ...)

Cellular Component (Gene Ontology)

GO-term

description

count in network

strength

signal

false discovery rate

GO:0005811

Lipid droplet

3 of 46

2.0

1.29

0.0032

Local Network Cluster (STRING)

cluster

description

count in network

strength

signal

false discovery rate

CL:14149

Phosphate acyltransferases, and glycerol-3-phosphate dehydrogenase complex

6 of 10

2.96

6.92

1.05e-13

CL:14113

Glycerophospholipid metabolism, and O-acyltransferase activity

8 of 68

2.25

5.98

4.67e-14

CL:14114

Glycerophospholipid metabolism

7 of 46

2.37

5.89

4.01e-13

CL:14153

Phosphate acyltransferases

4 of 5

3.09

4.57

4.25e-09

CL:2867

Alditol phosphate metabolic process, and Major intrinsic protein, conserved site

2 of 5

2.79

1.44

0.0024

KEGG Pathways

pathway

description

count in network

strength

signal

false discovery rate

map00561

Glycerolipid metabolism

9 of 99

2.14

6.46

1.12e-16

map00564

Glycerophospholipid metabolism

8 of 152

1.9

4.53

7.07e-13

map00565

Ether lipid metabolism

3 of 38

2.08

2.05

8.48e-05

map01110

Biosynthesis of secondary metabolites

7 of 1129

0.98

0.94

8.48e-05

map01100

Metabolic pathways

9 of 3880

0.55

0.43

0.0020

Reactome Pathways

pathway

description

count in network

strength

signal

false discovery rate

MAP-75109

Triglyceride biosynthesis

3 of 6

2.88

2.61

1.68e-05

MAP-8979227

Triglyceride metabolism

3 of 8

2.76

2.59

1.68e-05

MAP-1483206

Glycerophospholipid biosynthesis

4 of 92

1.82

1.87

9.46e-05

MAP-1483257

Phospholipid metabolism

4 of 122

1.7

1.68

0.00018

MAP-1482801

Acyl chain remodelling of PS

2 of 11

2.44

1.25

0.0049

(more ...)

Subcellular Localization (COMPARTMENTS)

compartment

description

count in network

strength

signal

false discovery rate

GOCC:0005811

Lipid droplet

4 of 37

2.22

2.53

1.03e-05

GOCC:0005783

Endoplasmic reticulum

4 of 311

1.29

0.85

0.0093

GOCC:0012505

Endomembrane system

5 of 831

0.96

0.58

0.0224

GOCC:0043229

Intracellular organelle

11 of 4988

0.53

0.43

0.00084

Protein Domains (Pfam)

domain

description

count in network

strength

signal

false discovery rate

PF02782

FGGY family of carbohydrate kinases, C-terminal domain

2 of 4

2.88

1.21

0.0066

PF00370

FGGY family of carbohydrate kinases, N-terminal domain

2 of 4

2.88

1.21

0.0066

Protein Domains and Features (InterPro)

domain

description

count in network

strength

signal

false discovery rate

IPR018483

Carbohydrate kinase, FGGY, conserved site

2 of 2

3.18

1.19

0.0073

IPR005999

Glycerol kinase

2 of 2

3.18

1.19

0.0073

IPR018485

Carbohydrate kinase, FGGY, C-terminal

2 of 4

2.88

1.18

0.0073

IPR018484

Carbohydrate kinase, FGGY, N-terminal

2 of 4

2.88

1.18

0.0073

IPR002123

Phospholipid/glycerol acyltransferase

2 of 6

2.71

1.18

0.0073

(more ...)

Protein Domains (SMART)

domain

description

count in network

strength

signal

false discovery rate

SM00563

Phosphate acyltransferases

3 of 7

2.82

2.75

8.82e-06

Enrichment display settings

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