Overview

Dataset statistics

Number of variables9
Number of observations144
Missing cells2
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.7 KiB
Average record size in memory75.9 B

Variable types

Numeric3
Categorical6

Dataset

Description농림식품 융복합 R&D 논문정보의(과제번호, 과제명, 연구책임자, 논문명, 학술지 출판년도, 저자, 학술지명)
Author농림식품기술기획평가원
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20191014000000001347

Alerts

분류 has constant value "농림식품 융복합" Constant
논문명 has a high cardinality: 126 distinct values High cardinality
저자 has a high cardinality: 119 distinct values High cardinality
학술지명 has a high cardinality: 89 distinct values High cardinality
과제명 is highly correlated with 분류 and 1 other fieldsHigh correlation
분류 is highly correlated with 과제명 and 2 other fieldsHigh correlation
학술지명 is highly correlated with 분류High correlation
연구책임자 is highly correlated with 과제명 and 1 other fieldsHigh correlation
저자 has 2 (1.4%) missing values Missing
번호 has unique values Unique

Reproduction

Analysis started2022-08-12 15:08:42.583703
Analysis finished2022-08-12 15:08:56.740999
Duration14.16 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

번호
Real number (ℝ≥0)

UNIQUE

Distinct144
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.5
Minimum1
Maximum144
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2022-08-13T00:08:56.956454image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.15
Q136.75
median72.5
Q3108.25
95-th percentile136.85
Maximum144
Range143
Interquartile range (IQR)71.5

Descriptive statistics

Standard deviation41.71330723
Coefficient of variation (CV)0.5753559618
Kurtosis-1.2
Mean72.5
Median Absolute Deviation (MAD)36
Skewness0
Sum10440
Variance1740
MonotonicityStrictly increasing
2022-08-13T00:08:57.304106image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11
 
0.7%
721
 
0.7%
31
 
0.7%
41
 
0.7%
51
 
0.7%
61
 
0.7%
71
 
0.7%
81
 
0.7%
101
 
0.7%
171
 
0.7%
Other values (134)134
93.1%
ValueCountFrequency (%)
11
0.7%
21
0.7%
31
0.7%
41
0.7%
51
0.7%
61
0.7%
71
0.7%
81
0.7%
91
0.7%
101
0.7%
ValueCountFrequency (%)
1441
0.7%
1431
0.7%
1421
0.7%
1411
0.7%
1401
0.7%
1391
0.7%
1381
0.7%
1371
0.7%
1361
0.7%
1351
0.7%

분류
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
농림식품 융복합
144 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row농림식품 융복합
2nd row농림식품 융복합
3rd row농림식품 융복합
4th row농림식품 융복합
5th row농림식품 융복합

Common Values

ValueCountFrequency (%)
농림식품 융복합144
100.0%

Length

2022-08-13T00:08:57.656820image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-13T00:08:57.954126image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
농림식품144
50.0%
융복합144
50.0%

과제번호
Real number (ℝ≥0)

Distinct12
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean192945.8333
Minimum112007
Maximum315074
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2022-08-13T00:08:58.161932image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum112007
5-th percentile112007
Q1112007
median113034
Q3313007
95-th percentile314033
Maximum315074
Range203067
Interquartile range (IQR)201000

Descriptive statistics

Standard deviation98606.41175
Coefficient of variation (CV)0.511057482
Kurtosis-1.865199274
Mean192945.8333
Median Absolute Deviation (MAD)1027
Skewness0.4007785511
Sum27784200
Variance9723224438
MonotonicityIncreasing
2022-08-13T00:08:58.450683image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
11200755
38.2%
31106319
 
13.2%
11303418
 
12.5%
11213612
 
8.3%
31305911
 
7.6%
31403310
 
6.9%
3130076
 
4.2%
3130225
 
3.5%
3130194
 
2.8%
3130412
 
1.4%
Other values (2)2
 
1.4%
ValueCountFrequency (%)
11200755
38.2%
11213612
 
8.3%
1130111
 
0.7%
11303418
 
12.5%
31106319
 
13.2%
3130076
 
4.2%
3130194
 
2.8%
3130225
 
3.5%
3130412
 
1.4%
31305911
 
7.6%
ValueCountFrequency (%)
3150741
 
0.7%
31403310
6.9%
31305911
7.6%
3130412
 
1.4%
3130225
 
3.5%
3130194
 
2.8%
3130076
 
4.2%
31106319
13.2%
11303418
12.5%
1130111
 
0.7%

과제명
Categorical

HIGH CORRELATION

Distinct12
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
스마트 실크 지지체와 골수유래 줄기세포를 이용한 바이오 뼈의 개발
55 
국내 식물자원 활용 만성감염바이러스 치료소재 개발 및 산업화
19 
국내산 식용 백장미로부터 피부미용 기능성을 갖는 이너뷰티(Inner Beauty) 소재 개발 및 제품화
18 
생강유래 불포화 케톤의 생물전환을 통한 뇌질환 개선 활성 대사체 생산 기술 개발
12 
융합통신기술과 RAD를 이용한 맞춤형 온실환경 제어모듈 실용화 기술 개발
11 
Other values (7)
29 

Length

Max length58
Median length57
Mean length37.86111111
Min length21

Unique

Unique2 ?
Unique (%)1.4%

Sample

1st row스마트 실크 지지체와 골수유래 줄기세포를 이용한 바이오 뼈의 개발
2nd row스마트 실크 지지체와 골수유래 줄기세포를 이용한 바이오 뼈의 개발
3rd row스마트 실크 지지체와 골수유래 줄기세포를 이용한 바이오 뼈의 개발
4th row스마트 실크 지지체와 골수유래 줄기세포를 이용한 바이오 뼈의 개발
5th row스마트 실크 지지체와 골수유래 줄기세포를 이용한 바이오 뼈의 개발

Common Values

ValueCountFrequency (%)
스마트 실크 지지체와 골수유래 줄기세포를 이용한 바이오 뼈의 개발55
38.2%
국내 식물자원 활용 만성감염바이러스 치료소재 개발 및 산업화19
 
13.2%
국내산 식용 백장미로부터 피부미용 기능성을 갖는 이너뷰티(Inner Beauty) 소재 개발 및 제품화18
 
12.5%
생강유래 불포화 케톤의 생물전환을 통한 뇌질환 개선 활성 대사체 생산 기술 개발12
 
8.3%
융합통신기술과 RAD를 이용한 맞춤형 온실환경 제어모듈 실용화 기술 개발11
 
7.6%
현장 이동형 농산물 원산지 판별기 개발10
 
6.9%
가축분뇨혐기소화액을 이용한 바이오연료용 미세조류 고밀도배양 기술 개발6
 
4.2%
저탄소·신가공 및 나노기술을 활용한 가공식품 개발5
 
3.5%
낙과(미숙과)를 이용한 고부가가치 뷰티케어 제품개발4
 
2.8%
생강나무 유래 심혈관 질환 치료제 후기 임상개발2
 
1.4%
Other values (2)2
 
1.4%

Length

2022-08-13T00:08:58.776255image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
개발137
 
10.6%
이용한76
 
5.9%
스마트55
 
4.2%
지지체와55
 
4.2%
골수유래55
 
4.2%
줄기세포를55
 
4.2%
바이오55
 
4.2%
뼈의55
 
4.2%
실크55
 
4.2%
및44
 
3.4%
Other values (74)653
50.4%

연구책임자
Categorical

HIGH CORRELATION

Distinct12
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
강길선
55 
강세찬
19 
이윤복
18 
하상근
12 
정선옥
11 
Other values (7)
29 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)1.4%

Sample

1st row강길선
2nd row강길선
3rd row강길선
4th row강길선
5th row강길선

Common Values

ValueCountFrequency (%)
강길선55
38.2%
강세찬19
 
13.2%
이윤복18
 
12.5%
하상근12
 
8.3%
정선옥11
 
7.6%
김영호10
 
6.9%
김성천6
 
4.2%
민상기5
 
3.5%
이기선4
 
2.8%
문홍식2
 
1.4%
Other values (2)2
 
1.4%

Length

2022-08-13T00:08:59.117844image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강길선55
38.2%
강세찬19
 
13.2%
이윤복18
 
12.5%
하상근12
 
8.3%
정선옥11
 
7.6%
김영호10
 
6.9%
김성천6
 
4.2%
민상기5
 
3.5%
이기선4
 
2.8%
문홍식2
 
1.4%
Other values (2)2
 
1.4%

논문명
Categorical

HIGH CARDINALITY

Distinct126
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Identification of endocrine disrupting chemicals using a virus-based colorimetric sensor
 
3
Bioinspired M-13 bacteriophage-based Photonic Nose for Differential Cell Recognition
 
3
Pharmacological advantages of melatonin in immunosenescence by improving activity of T lymphocytes
 
2
Antiplatelet and Antithrombotic Effects of the Extract of Lindera obtusiloba Leaves
 
2
Isolation and characterization of human intestinal Enterococcus avium EFEL009 converting rutin to quercetin
 
2
Other values (121)
132 

Length

Max length205
Median length117
Mean length93.6875
Min length19

Unique

Unique110 ?
Unique (%)76.4%

Sample

1st rowEnhanced osteogenesis of b-tricalcium phosphate reinforced silkfibroin scaffold for bone tissue biofabrication
2nd row실크필름에 배양한 망막색소상피세포의 거동
3rd rowFabrication of 3D porous SF/-TCP hybrid scaffolds for bone tissue reconstruction
4th rowPressure and temperature dependences of the acoustic behaviors of biocompatible silk studied by using Brillouin spectroscopy
5th rowThe Role of demineralized bone particle in a PLGA scaffold designed to create a media equivalent for a tissue engineering blood vessel

Common Values

ValueCountFrequency (%)
Identification of endocrine disrupting chemicals using a virus-based colorimetric sensor3
 
2.1%
Bioinspired M-13 bacteriophage-based Photonic Nose for Differential Cell Recognition3
 
2.1%
Pharmacological advantages of melatonin in immunosenescence by improving activity of T lymphocytes2
 
1.4%
Antiplatelet and Antithrombotic Effects of the Extract of Lindera obtusiloba Leaves2
 
1.4%
Isolation and characterization of human intestinal Enterococcus avium EFEL009 converting rutin to quercetin2
 
1.4%
Characterization of metabolites produced from the biotransformation of 6-shogaol formed by Aspergillus niger2
 
1.4%
M-13 bacteriophage based structural color sensor for detecting antibiotics2
 
1.4%
Effect of Pore Sizes of Silk Scaffolds for Cartilage Tissue Engineering2
 
1.4%
오리발 유래 콜라겐/락타이드 글리콜라이드 공중합체 지지체에서의 골분화능 효과2
 
1.4%
Endothelium-Dependent Vasorelaxant Effects of Dealcoholized Wine Powder of Wild Grape (Vitis coignetiae) in the Rat Thoracic Aorta2
 
1.4%
Other values (116)122
84.7%

Length

2022-08-13T00:08:59.472666image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
of139
 
7.6%
and51
 
2.8%
in46
 
2.5%
the30
 
1.6%
for30
 
1.6%
a24
 
1.3%
extract14
 
0.8%
using13
 
0.7%
from13
 
0.7%
silk13
 
0.7%
Other values (817)1446
79.5%

학술지 출판년도
Real number (ℝ≥0)

Distinct6
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2014.861111
Minimum2012
Maximum2017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2022-08-13T00:08:59.803771image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum2012
5-th percentile2013
Q12014
median2015
Q32016
95-th percentile2017
Maximum2017
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.249397679
Coefficient of variation (CV)0.0006200912174
Kurtosis-0.4356066735
Mean2014.861111
Median Absolute Deviation (MAD)1
Skewness-0.4312596214
Sum290140
Variance1.560994561
MonotonicityNot monotonic
2022-08-13T00:09:00.084522image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
201544
30.6%
201641
28.5%
201427
18.8%
201317
 
11.8%
20179
 
6.2%
20126
 
4.2%
ValueCountFrequency (%)
20126
 
4.2%
201317
 
11.8%
201427
18.8%
201544
30.6%
201641
28.5%
20179
 
6.2%
ValueCountFrequency (%)
20179
 
6.2%
201641
28.5%
201544
30.6%
201427
18.8%
201317
 
11.8%
20126
 
4.2%

저자
Categorical

HIGH CARDINALITY
MISSING

Distinct119
Distinct (%)83.8%
Missing2
Missing (%)1.4%
Memory size1.2 KiB
문종식
 
4
김종윤
 
3
문진석
 
3
차세호
 
2
송정은;
 
2
Other values (114)
128 

Length

Max length53
Median length26
Mean length7.577464789
Min length3

Unique

Unique100 ?
Unique (%)70.4%

Sample

1st rowDae Hoon Lee;
2nd row이소진;
3rd row박현정;
4th rowByoung Wan Lee;
5th row조한수;

Common Values

ValueCountFrequency (%)
문종식4
 
2.8%
김종윤3
 
2.1%
문진석3
 
2.1%
차세호2
 
1.4%
송정은;2
 
1.4%
장나금;2
 
1.4%
정현기;2
 
1.4%
신동명2
 
1.4%
장지은;2
 
1.4%
김도경2
 
1.4%
Other values (109)118
81.9%

Length

2022-08-13T00:09:00.503894image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
kim16
 
6.2%
jae8
 
3.1%
park6
 
2.3%
lee5
 
1.9%
eun5
 
1.9%
hyun4
 
1.6%
jeong4
 
1.6%
min4
 
1.6%
문종식4
 
1.6%
cha4
 
1.6%
Other values (149)198
76.7%

학술지명
Categorical

HIGH CARDINALITY
HIGH CORRELATION

Distinct89
Distinct (%)61.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
International Journal of Tissue Regeneration
12 
폴리머 = Polymer (Korea)
 
7
International Journal of Tissue Regeneration,
 
6
Polymer(Korea)
 
4
Laboratory animal research
 
3
Other values (84)
112 

Length

Max length73
Median length51
Mean length30.26388889
Min length5

Unique

Unique61 ?
Unique (%)42.4%

Sample

1st rowINTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES
2nd row폴리머 = Polymer (Korea)
3rd rowJOURNAL OF BIOMEDICAL MATERIALS RESEARCH PART A
4th rowJOURNAL OF THE KOREAN PHYSICAL SOCIETY
5th rowMACROMOLECULAR RESEARCH

Common Values

ValueCountFrequency (%)
International Journal of Tissue Regeneration12
 
8.3%
폴리머 = Polymer (Korea)7
 
4.9%
International Journal of Tissue Regeneration,6
 
4.2%
Polymer(Korea)4
 
2.8%
Laboratory animal research3
 
2.1%
Macromolecular research3
 
2.1%
Chemical Science3
 
2.1%
MACROMOLECULAR RESEARCH3
 
2.1%
원예과학기술지3
 
2.1%
CHEMISTRY-AN ASIAN JOURNAL3
 
2.1%
Other values (79)97
67.4%

Length

2022-08-13T00:09:00.859870image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
journal53
 
9.9%
of48
 
9.0%
and26
 
4.9%
research26
 
4.9%
international23
 
4.3%
tissue19
 
3.6%
regeneration18
 
3.4%
science15
 
2.8%
13
 
2.4%
polymer10
 
1.9%
Other values (137)283
53.0%

Interactions

2022-08-13T00:08:54.338663image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-08-13T00:08:52.175788image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-08-13T00:08:53.453389image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-08-13T00:08:54.719189image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-08-13T00:08:52.653333image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-08-13T00:08:53.758600image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-08-13T00:08:55.097358image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-08-13T00:08:53.146594image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-08-13T00:08:54.070183image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Correlations

2022-08-13T00:09:01.202550image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-08-13T00:09:01.506123image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-08-13T00:09:01.866702image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-08-13T00:09:02.188019image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2022-08-13T00:09:02.495713image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2022-08-13T00:08:55.700507image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
A simple visualization of nullity by column.
2022-08-13T00:08:56.317961image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-08-13T00:08:56.586488image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

번호분류과제번호과제명연구책임자논문명학술지 출판년도저자학술지명
01농림식품 융복합112007스마트 실크 지지체와 골수유래 줄기세포를 이용한 바이오 뼈의 개발강길선Enhanced osteogenesis of b-tricalcium phosphate reinforced silkfibroin scaffold for bone tissue biofabrication2016Dae Hoon Lee;INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES
12농림식품 융복합112007스마트 실크 지지체와 골수유래 줄기세포를 이용한 바이오 뼈의 개발강길선실크필름에 배양한 망막색소상피세포의 거동2014이소진;폴리머 = Polymer (Korea)
23농림식품 융복합112007스마트 실크 지지체와 골수유래 줄기세포를 이용한 바이오 뼈의 개발강길선Fabrication of 3D porous SF/-TCP hybrid scaffolds for bone tissue reconstruction2016박현정;JOURNAL OF BIOMEDICAL MATERIALS RESEARCH PART A
34농림식품 융복합112007스마트 실크 지지체와 골수유래 줄기세포를 이용한 바이오 뼈의 개발강길선Pressure and temperature dependences of the acoustic behaviors of biocompatible silk studied by using Brillouin spectroscopy2016Byoung Wan Lee;JOURNAL OF THE KOREAN PHYSICAL SOCIETY
45농림식품 융복합112007스마트 실크 지지체와 골수유래 줄기세포를 이용한 바이오 뼈의 개발강길선The Role of demineralized bone particle in a PLGA scaffold designed to create a media equivalent for a tissue engineering blood vessel2015조한수;MACROMOLECULAR RESEARCH
56농림식품 융복합112007스마트 실크 지지체와 골수유래 줄기세포를 이용한 바이오 뼈의 개발강길선Skin Regeneration Using Duck’s Feet Derived Collagen andPoly(vinyl alcohol) Scaffold2015송정은;MACROMOLECULAR RESEARCH
67농림식품 융복합112007스마트 실크 지지체와 골수유래 줄기세포를 이용한 바이오 뼈의 개발강길선Dissolution Properties of Lercanidipine Solid Dispersion Manufactured Water - Soluble Polymer PVP K-302015정현기;POLYMER-KOREA
78농림식품 융복합112007스마트 실크 지지체와 골수유래 줄기세포를 이용한 바이오 뼈의 개발강길선Evaluation of the Therapeutic Potential In vitro and In vivo of the SIS/PLGA Scaffolds for Costal Cartilage Regeneration2016차세롬;MACROMOLECULAR RESEARCH
89농림식품 융복합112007스마트 실크 지지체와 골수유래 줄기세포를 이용한 바이오 뼈의 개발강길선A Study on Release Behavior of Olmesartan Loaded Polyoxalate Microspheres2015김창현;International Journal of Tissue Regeneration
910농림식품 융복합112007스마트 실크 지지체와 골수유래 줄기세포를 이용한 바이오 뼈의 개발강길선Controlled Release of Loxoprofen Sodium using Triple Layer byWet Granulation2015정현기;International Journal of Tissue Regeneration

Last rows

번호분류과제번호과제명연구책임자논문명학술지 출판년도저자학술지명
134135농림식품 융복합314033현장 이동형 농산물 원산지 판별기 개발김영호Formation of water soluble wavelength tunable InGaP and InP quantum dots2016문종식Polymer Bulletin
135136농림식품 융복합314033현장 이동형 농산물 원산지 판별기 개발김영호Bioinspired M-13 bacteriophage-based Photonic Nose for Differential Cell Recognition2016문종식Chemical Science
136137농림식품 융복합314033현장 이동형 농산물 원산지 판별기 개발김영호Bioinspired M-13 bacteriophage-based Photonic Nose for Differential Cell Recognition2016신동명Chemical Science
137138농림식품 융복합314033현장 이동형 농산물 원산지 판별기 개발김영호Bioinspired M-13 bacteriophage-based Photonic Nose for Differential Cell Recognition2016이소영Chemical Science
138139농림식품 융복합314033현장 이동형 농산물 원산지 판별기 개발김영호Identification of endocrine disrupting chemicals using a virus-based colorimetric sensor2016문종식CHEMISTRY-AN ASIAN JOURNAL
139140농림식품 융복합314033현장 이동형 농산물 원산지 판별기 개발김영호Identification of endocrine disrupting chemicals using a virus-based colorimetric sensor2016이유진CHEMISTRY-AN ASIAN JOURNAL
140141농림식품 융복합314033현장 이동형 농산물 원산지 판별기 개발김영호Identification of endocrine disrupting chemicals using a virus-based colorimetric sensor2016신동명CHEMISTRY-AN ASIAN JOURNAL
141142농림식품 융복합314033현장 이동형 농산물 원산지 판별기 개발김영호M-13 bacteriophage based structural color sensor for detecting antibiotics2016박민지Sensors and Actuators B: Chemical
142143농림식품 융복합314033현장 이동형 농산물 원산지 판별기 개발김영호M-13 bacteriophage based structural color sensor for detecting antibiotics2016문종식Sensors and Actuators B: Chemical
143144농림식품 융복합315074제주산 흑무(black radish) 및 유색무(color radish) 육성을 통한 기능성식품개발 기획김기옥CURRENT POTENTIAL HEALTH BENEFITS OF SULFORAPHANE2016Jae Kwang KimExperimental and Clinical Sciences, International Online Journal