May 2, 2015 - University Medical Center, Amsterdam, the Netherlands. 4Department of ...... Fields KB, Sykes JC, Walker KM, Jackson JC. Prevention of ..... A JOSPT subscriber: Email your request to [email protected] or call the JOSPT o ce ...
sooner will compete more effectively than words that are only activated later. However ..... 80% correct responses across participants was removed, and only the ...
6/16/2013 4:27 PM. See change log on last page(s). Items suggested for change
or questions are highlighted in colors. JSOC Keywords used for metadata.
Robert Harland Testing keywords internationally to define and apply undergraduate assessment standards in art and design www.FORMakademisk.org. 1. Vol.
Jun 3, 2016 - f Health eResearch Centre, Farr Institute for Health Informatics Research, ... E-mail address: [email protected] (W.G. Dixon). ...... Wende, J. Robbins, F.A. Hubbell, L. Nathan, R.D. Langer, M. Gass, M. Limacher, D.
Edfu (Upper Egypt). 131 BCE. Throughout Egypt. 107 BCE. Upper Egypt. 84 BCE**. Middle Egypt. Source: Adapted (see Methods) from Anne-Emmanuelle ...
May 7, 2010 - A Call to Standardize Teratoma Assays. Used to Define Human Pluripotent Cell Lines. Franz-Josef Mu¨ ller,1,2,* Johanna Goldmann,1 Peter ...
ATCC. See ref. Gazdar et al, 1998. HCC1419. Breast. ATCC. See ref. Gazdar et al ... ATCC. DMEM/F12 Fogh and Trempe 1975. SUM159. Breast. Orig. See ref.
I24.1 Dressler's syndrome. I24.8 Other forms of acute ischaemic heart disease. I24.9 Acute ischaemic heart disease, unspecified. I25 Chronic ischaemic heart ...
Page 1. 1. Supplementary Table 1. PCR primers used to detect mouse gene expressions. Gene. Forward ... UDP glucuronosyltransferase 1 family polypeptide A1.
Dec 1, 2014 - Firehouse Subs. Captain D's. Pei Wei. Boston Market. Serrano and Jedda, 2009 [18]. Jan 2006 (period of interest) data were also collected in.
Page 1 ... Why: Your keywords should reflect all of the different types of user queries that could ... Don't create minu
Search engine marketers should consider these points to get the most out of their keywords. If you want to learn more, d
Communication and information technology; adaptive learning; self-driven learning; .... which is provided mostly by engineering, will be accelerated; because of the many new .... upon fulfillment of the study plan requirements of the program.
Appendix: Description of OPCS codes used to define breast excision procedures ... B28.4. Re-excision of breast margins. Codes indicating laterality. Z94.2.
Diagnostic groups: Diverticular disease of the colon with perforation (cohort defining variable): ICD-8: 562.12; ICD-10: K57.2, K57.4. Diverticular disease of the ...
CORNELIA M. WEYAND, JORG GORONZY, AND C. GARRISON FATHMAN. Department of Medicine, Division of Immunology, Stanford University Medical ...
galectin-4 (Gal-4) organizes the transport of axon glycoproteins by binding to N- ... The role of these membrane Gal-4-containing domains (G4Ds) is unknown ...
b Values for EAR are adjusted for an assumed bioavailability (WHO/FAO, 2004). ... d One μg retinol equivalent (RE) is equal to 1 μg all-trans-retinol, 6 μg β-carotene ... from a basis of 22 mg/d for an average bioavailability assumed to be 23%.
Table 1. Keywords used to define segments the epigenetics database ...
Keywords for Hotspot Map Table Columns. CANCER BLADDER CANCER
CARCINOMA BREAST CANCER
ADENOCARCINOMA BURKITT LYMPHOMA
ANGIOGENESIS CERVICAL CANCER
COLON CANCER EPITHELIAL*MESENCHYMAL
COLORECTAL CANCER ESOPHAGEAL CANCER, ESOPHAGEAL CANCER HEPATOCELLULAR CARCINOMA MYELODYSPLASTIC OVARIAN CANCER TUMOR SUPPRESSOR PREVENTION & CANCER AUTISIM BONE MARROW MYOCARDIAL INFARCTION COMPANION DIAGNOSTIC HEPATITIS PREDICTIVE BIOMARKER
EMT GASTRIC CANCER
ENDOMETRIAL CANCER GASTROINTESTINAL CANCER
B‐CELL LYMPHOMA CHRONIC LYMPHOCYTIC LEUKEMIA EPITHELIAL CANCER GLIOBLASTOMA
LEUKEMIA MYELOID LEUKEMIA PANCREATIC CANCER DEVELOPMENT & CANCER PROGRESSION & CANCER NEURODEGENERATIVE CARDIOVASCULAR AGING, AGE RELATED DIABETES INFLAMMATION PROGNOSTIC BIOMARKER
LUNG CANCER NECK CANCER PROSTATE CANCER EPIGENETIC CANCER RISK & CANCER NEUROLOGICAL DISEASE HEMATOPOIESIS ALLERGY DISEASE MICROVESICLE SCHIZOPHRENIA
MELANOMA NON SMALL CELL LUNG CANCER SQUAMOUS CELL CARCINOMA GENE & CANCER TUMOR & CANCER NEURONAL HEMATOPOIETIC APOPTOSIS EXOSOME OBESITY STEM CELL
HEPATIC CANCER METASTASIS ORAL CANCER THYROID CANCER HYPERMETHYLATION & CANCER ALZHEIMER PARKINSON HYPERTENSI AUTOIMMUN HEART DISEASE PHARMACODYNAMIC BIOMARKER MATERNAL
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
2
0
0
0
0
0
0
0
10
7
36
5
54
0
0
CHROMODOMAIN
0
0
0
TUDOR DOMAIN
1
0
0
0
0
0
0
0
0
0
0
0
0
0
1898
299
61
77
16
22
211
5
20
15
64
91
18
HISTONE HISTONE H1
1
0
375
20
754
498
18
2
118
162
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3
0
0
0
0
1
0
0
0
0
0
0
0
0
1
3
0
0
0
1
0
1
0
0
0
0
0
0
0
1
0
0
3
2
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
1
10
0
0
58
320
90
54
115
74
98
7
21
8
50
36
149
36
15
435
224
105
708
57
415
202
1295
169
19
88
51
271
3
0
0
0
0
4
0
1
0
0
1
0
0
0
7
1
0
1
0
0
7
3
0
0
0
5
0
0
1
0
0
0
0
0
639
16
1588
295
85
376
125
937
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
3
0
0
1
0
0
0
0
0
0
0
1
0
0
4
4
0
10
4
2
7
16
9
1
4
53
2
1
1
16
23
7
1
2
12
1
17
3
0
0
15
84
13
7
21
6
22
1
5
0
12
5
35
10
2
84
78
0
267
44
7
61
20
178
4
1
0
0
12
0
1
0
5
5
0
0
0
1
0
1
1
0
0
2
12
2
0
6
1
3
0
1
0
1
0
1
3
0
11
11
0
39
13
2
10
5
38
HISTONE MODIFICATION
592
80
20
15
2
5
59
1
3
3
20
37
4
1
4
11
1
14
3
0
0
16
63
20
11
35
14
19
1
3
1
18
4
47
9
3
129
208
5
527
114
34
131
56
288
82
19
18
6
10
21
21
7
4
1
8
12
0
0
1
53
2
12
1
33
2
6
0
127
24
5
2
0
1
20
0
1
2
11
6
0
3
0
2
0
8
0
0
0
2
22
6
6
6
5
7
HISTONE & METHYLATION
1117
168
30
28
3
11
127
2
14
8
46
66
6
7
5
17
3
42
9
0
0
34
156
47
27
66
46
47
IMPORTIN
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
KARYOPHERIN
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
NUCLEAR PORE
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
NUCLEAR PORE COMPLEX
6
4
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
2
0
1
0
METHYLAT (CHEM MODIF)
4261
1245
269
77
38
85
530
10
74
39
211
482
24
38
24
56
32
236
33
2
1
208
454
325
112
284
PHOSPHORYLAT (CHEM MODI
180
51
10
7
0
0
21
0
1
1
8
8
4
0
0
9
2
5
1
0
0
9
19
9
5
SUMOYLAT (CHEM MODIF)
13
0
0
0
0
0
2
0
0
0
0
0
1
0
0
1
0
0
0
0
0
0
0
0
0
UBIQUITYLAT (CHEM MODIF) DNA METHYLAT (CHEM MODIF DNA PHOSPHORYLAT (CHEM M DNA SUMOYLAT (CHEM MODIF DNA UBIQUITYLAT (CHEM MOD
228
43
7
0
0
16
2
0
0
3
15
3
0
0
12 9
84
27
25
20
12
23
13
9
15
10
28
2
7
9
1
5
2
1
2
1
5
2
14
6
9
4
3
35
13
18
82
7
42 24
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
0
0
0
0
118
152
39
99
25
162
17
3
5
0
2
1
1
0
0
0
0
0
92
4
4
387
2
1
200
2
0
36
36
5
106
28
5
20
5
72
6
280
381
10
998
240
61
223
85
577
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3
2
0
6
2
0
0
0
5
71
258
240
33
1307
1229
25
3727
1425
167
834
505
2497
2
4
12
10
0
56
52
1
136
16
3
39
8
95
0
0
2
0
0
4
7
0
12
0
1
2
0
73
23 8
82
2
4
67
62
0
12
81
135
0
20
8
9
4
2
4
HISTONE & DEMETHYLATION
0
41
1665
430
20
HISTONE & DEACETYLATION
0
546
1715
69
1
1
951
7 4
55
10
0
1
280
15
2
0
10
149
24
0
319
6
0
49
134
11
0
HISTONE H4
2
0
64
25
15
0
HISTONE H3
476
0
22
79
5
0
HISTONE H2
HISTONE & ACETYLATION
4
47
13
6
0
PROGRESSION & CANCER
0
0
4
55
7
0
PREVENTION & CANCER
1
0
21
27
21
0
EPIGENETIC CANCER
0
0
8
66
12
0
DEVELOPMENT & CANCER
0
0
31
53
24
0
PROSTATE CANCER
0
0
0
19
141
10
0
LEUKEMIA
BREAST CANCER
0
0
0
79
39
27
0
HEPATOCELLULAR CARCINOMA
BLADDER CANCER
0
0
0
26
176
59
0
HEPATIC CANCER
B-CELL LYMPHOMA
0
0
0
63
151
17
GLIOBLASTOMA
ANGIOGENESIS
0
0
0
EMT
ADENOCARCINOMA
0
0
4
CARCINOMA
0
2
7
CANCER
0
10
112
113
1
TUMOR & CANCER
0
1
BROMODOMAIN
59
1
1
RISK & CANCER
0
PRION
1
0
1
HYPERMETHYLATION & CANCER
0
GENE & CANCER
0
0
TUMOR SUPPRESSOR
2
0
THYROID CANCER
15
11
0
0
SQUAMOUS CELL CARCINOMA
15
136
0
0
3
0
PANCREATIC CANCER
63
21
3
0
82
0
OVARIAN CANCER
6
29
1
0
251
12
0
ORAL CANCER
GASTROINTESTINAL CANCER
14
12
2
0
134
48
10
0
NON SMALL CELL LUNG CANCER
GASTRIC CANCER
9
25
1
0
16
26
5
1
NECK CANCER
EPITHELIAL*MESENCHYMAL
11
11
44
0
14
36
25
0
MYELOID LEUKEMIA
EPITHELIAL CANCER
6
222
19
0
20
160
114
4
MYELODYSPLASTIC
COLORECTAL CANCER 184
89
11
74
694
490
METASTASIS
COLON CANCER 79
10
6 0
339
1854
METHYLATION PATTERN
MELANOMA
CHRONIC LYMPHOCYTIC LEUKEMIA 14
41
1046
HYPERMETHYLAT
LUNG CANCER
CERVICAL CANCER 16
7
ENDOMETRIAL CANCER
BURKITT LYMPHOMA 3
CPG ISLAND
PIWI
ESOPHAGEAL CANCER, ESOPHAGEAL CANCER
Figure 2. Excerpt of the Technology Publication Hotspot Map for Epigenetics Space.
48
22
244
5
152
0 0
3
5
2
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
1
0
0
5
3
0
5
0
0
0
1
3
2807
636
140
51
23
45
341
8
44
28
125
271
18
20
15
38
15
140
19
0
1
126
295
173
69
167
88
97
23
45
11
102
44
175
117
15
765
866
20
2455
879
129
528
359
1540
11
15
48 6
14
1
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
3
5
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
1
0
0
3
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
1
0
0
2
0
0
0
0
0
37
9
5
1
3
23
0
3
2
13
15
0
0
1
3
1
4
3
0
0
4
24
9
4
13
7
6
1
4
2
3
4
9
5
1
60
97
3
196
59
5
43
15
103
0
5
1
1
6
0
0
0
0
1
2
0
0
2
0
0
1
0
0
4
20
1
0
1
1
7
0
0
2
1
1
7
1
0
10
21
0
64
6
4
9
8
29
6
26
28
9
7
4
20
4
0
0
26
132
44
44
1
8
3
19
26
72
14
10
182
235
8
598
116
34
147
25
403
3
0
0
0
2
METHYLAT* CYTOSINE
235
ACETYLTRANSFERASE
75
8
DEACETYLASE
756
125
4 1
0 0
0
1
2
0
1
0
1
0
4
3
0
1
0
37 6
7
1
9 1
3 0
17 0
30
48
7
12
84
1
14
14
2
39
28
51
DEMETHYLASE (ENZ)
116
17
3
3
1
1
12
0
1
0
3
5
0
5
0
4
0
2
15
2
2
3
0
1
0
5
0
24
1
94
14
2
19
6
54
DNMT1_3A_3B
248
64
15
5
3
4
31
0
8
3
17
26
1
4
2
2
0
12
1
0
0
18
40
17
6
9
15
18
2
4
0
2
5
11
8
0
105
62
6
206
74
9
31
28
147
HISTONE ACETYLTRANSFERAS
68
7
0
5
1
0
6
0
0
0
0
1
2
0
0
2
0
0
1
0
0
3
18
1
0
1
1
6
0
0
1
1
1
7
1
0
9
19
0
58
6
3
9
6
29
HISTONE DEACETYLASE (EPIG
784
131
30
48
8
12
97
1
15
7
27
33
10
8
4
15
2
22
5
0
0
25
139
41
29
54
46
47
1
9
3
21
27
77
15
7
190
229
8
616
119
34
152
24
419
HISTONE DEMETHYLASE (ENZ
64
HISTONE METHYLTRANSFERA
105
METHYLASE METHYLTRANSFERASE
7
0
0
0
2
0
2
0
0
0
0
3
1
1
7
1
0
3
2
1
12
0
1
1
6
1
0
0
2
0
3
0
0
0
11
0
1
1
0
0
2
0
0
1
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
1
2
0
0
1
0
0
0
0
0
0
2
1
0
0
4
1
0
6
0
0
1
0
2
24
8
7
92
3
8
4
34
63
5
7
3
8
2
37
4
2
1
41
140
44
22
39
52
47
2
8
2
15
19
41
17
2
244
222
22
658
221
26
113
65
440
36
2 8
2
1
2
12
0 5
0
0
0
0
0 0
0
2
1
10
1
0
15
40
30
4
10
2
2
3
2
2
153
1
1
6
2
0
0
775
8
0
0
35
21 32
0 1
48 89
5 12
0 0
12
3
26
13
29 60
FFigure 3. Measurring the speed off publication for sselected segmentts relative to the entire epigeneticc database (see FFig. 1). The measurement for eeach segment ressults in a rating th hat runs from +1 to ‐1. A “+1” rating means that ssegment is growiing much faster tthan might be expected from tthe database as a whole. A “‐1”” rating means that growth is much below the database d as whoole. A “0” ratingg means that thee segment is ggrowing at the saame speed as the e epigenetics dataabase. Fig. 3a ggives measurements for some of tthe epigenetic “m machinery” components. Fig. 3 3b gives acceleration measurements for selected ttarget disease staates.
