Overview

Dataset statistics

Number of variables9
Number of observations164
Missing cells3
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.1 KiB
Average record size in memory75.8 B

Variable types

Numeric3
Categorical6

Dataset

Description농림식품 수의학 R&D 논문정보의(과제번호, 과제명, 연구책임자, 논문명, 학술지 출판년도, 저자, 학술지명)
Author농림식품기술기획평가원
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20191014000000001338

Alerts

분류 has constant value "수의" Constant
논문명 has a high cardinality: 150 distinct values High cardinality
저자 has a high cardinality: 125 distinct values High cardinality
학술지명 has a high cardinality: 108 distinct values High cardinality
연구책임자 is highly correlated with 과제명 and 1 other fieldsHigh correlation
과제명 is highly correlated with 연구책임자 and 1 other fieldsHigh correlation
분류 is highly correlated with 연구책임자 and 1 other fieldsHigh correlation
저자 has 3 (1.8%) missing values Missing
번호 has unique values Unique

Reproduction

Analysis started2022-08-12 14:49:05.568172
Analysis finished2022-08-12 14:49:08.714895
Duration3.15 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

번호
Real number (ℝ≥0)

UNIQUE

Distinct164
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82.5
Minimum1
Maximum164
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2022-08-12T23:49:08.819773image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.15
Q141.75
median82.5
Q3123.25
95-th percentile155.85
Maximum164
Range163
Interquartile range (IQR)81.5

Descriptive statistics

Standard deviation47.48684028
Coefficient of variation (CV)0.575598064
Kurtosis-1.2
Mean82.5
Median Absolute Deviation (MAD)41
Skewness0
Sum13530
Variance2255
MonotonicityStrictly increasing
2022-08-12T23:49:09.070905image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11
 
0.6%
201
 
0.6%
31
 
0.6%
41
 
0.6%
51
 
0.6%
61
 
0.6%
71
 
0.6%
81
 
0.6%
91
 
0.6%
111
 
0.6%
Other values (154)154
93.9%
ValueCountFrequency (%)
11
0.6%
21
0.6%
31
0.6%
41
0.6%
51
0.6%
61
0.6%
71
0.6%
81
0.6%
91
0.6%
101
0.6%
ValueCountFrequency (%)
1641
0.6%
1631
0.6%
1621
0.6%
1611
0.6%
1601
0.6%
1591
0.6%
1581
0.6%
1571
0.6%
1561
0.6%
1551
0.6%

분류
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
수의
164 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
수의164
100.0%

Length

2022-08-12T23:49:09.431307image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-12T23:49:09.591762image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
수의164
100.0%

과제번호
Real number (ℝ≥0)

Distinct10
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean299561.9146
Minimum112131
Maximum313060
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2022-08-12T23:49:09.721051image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum112131
5-th percentile112576.2
Q1311007
median311011
Q3313013
95-th percentile313016
Maximum313060
Range200929
Interquartile range (IQR)2006

Descriptive statistics

Standard deviation47841.83429
Coefficient of variation (CV)0.1597059972
Kurtosis11.85000923
Mean299561.9146
Median Absolute Deviation (MAD)4
Skewness-3.701145148
Sum49128154
Variance2288841108
MonotonicityIncreasing
2022-08-12T23:49:09.874475image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
31100758
35.4%
31101142
25.6%
31301418
 
11.0%
31301312
 
7.3%
1121319
 
5.5%
3130058
 
4.9%
3130607
 
4.3%
3130165
 
3.0%
3130154
 
2.4%
1150991
 
0.6%
ValueCountFrequency (%)
1121319
 
5.5%
1150991
 
0.6%
31100758
35.4%
31101142
25.6%
3130058
 
4.9%
31301312
 
7.3%
31301418
 
11.0%
3130154
 
2.4%
3130165
 
3.0%
3130607
 
4.3%
ValueCountFrequency (%)
3130607
 
4.3%
3130165
 
3.0%
3130154
 
2.4%
31301418
 
11.0%
31301312
 
7.3%
3130058
 
4.9%
31101142
25.6%
31100758
35.4%
1150991
 
0.6%
1121319
 
5.5%

과제명
Categorical

HIGH CORRELATION

Distinct10
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
가축전염병 제어용 신소재를 이용한 백신기능 면역복합제제 개발
58 
인체질병 적용 실험동물 모델 개발
42 
고효율 미생물 발현시스템을 이용한 효과적인 가축점막면역백신의 개발
18 
오리의 고병원성 조류인플루엔자 및 살모넬라 백신 개발
12 
병원체 특이 박테리오파지를 이용한 돼지 세균성 병원체 제어제 개발
9 
Other values (5)
25 

Length

Max length57
Median length50
Mean length31.46341463
Min length18

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st row병원체 특이 박테리오파지를 이용한 돼지 세균성 병원체 제어제 개발
2nd row병원체 특이 박테리오파지를 이용한 돼지 세균성 병원체 제어제 개발
3rd row병원체 특이 박테리오파지를 이용한 돼지 세균성 병원체 제어제 개발
4th row병원체 특이 박테리오파지를 이용한 돼지 세균성 병원체 제어제 개발
5th row병원체 특이 박테리오파지를 이용한 돼지 세균성 병원체 제어제 개발

Common Values

ValueCountFrequency (%)
가축전염병 제어용 신소재를 이용한 백신기능 면역복합제제 개발58
35.4%
인체질병 적용 실험동물 모델 개발42
25.6%
고효율 미생물 발현시스템을 이용한 효과적인 가축점막면역백신의 개발18
 
11.0%
오리의 고병원성 조류인플루엔자 및 살모넬라 백신 개발12
 
7.3%
병원체 특이 박테리오파지를 이용한 돼지 세균성 병원체 제어제 개발9
 
5.5%
돼지생식기호흡기증후군(PRRS) 발생위험도평가프로그램개발 및 바이러스 단백질 기능저해제개발8
 
4.9%
다축종 (산업동물 및 반려동물 포함) 적용 가능한 신속, 정확한 인플루엔자 검출 기법 개발 및 상용화7
 
4.3%
국내분리 H5N1형 HPAI의 주요 야생조류 종별 병원성 및 병리기전 구명5
 
3.0%
구제역바이러스 비구조단백질을 표적으로 하는 항바이러스제 개발4
 
2.4%
축종(오리,육계,토종닭 등) 최적 소독 및 방역관리 모델 개발1
 
0.6%

Length

2022-08-12T23:49:10.060536image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-12T23:49:10.315417image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
개발151
 
13.2%
이용한85
 
7.4%
가축전염병58
 
5.1%
면역복합제제58
 
5.1%
제어용58
 
5.1%
백신기능58
 
5.1%
신소재를58
 
5.1%
적용49
 
4.3%
모델43
 
3.8%
인체질병42
 
3.7%
Other values (53)482
42.2%

연구책임자
Categorical

HIGH CORRELATION

Distinct9
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
박최규
58 
이병천
42 
최윤재
18 
김원일
17 
송창선
12 
Other values (4)
17 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
박최규58
35.4%
이병천42
25.6%
최윤재18
 
11.0%
김원일17
 
10.4%
송창선12
 
7.3%
박현규7
 
4.3%
김재홍5
 
3.0%
정귀완4
 
2.4%
조창호1
 
0.6%

Length

2022-08-12T23:49:10.581255image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-12T23:49:10.815096image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
박최규58
35.4%
이병천42
25.6%
최윤재18
 
11.0%
김원일17
 
10.4%
송창선12
 
7.3%
박현규7
 
4.3%
김재홍5
 
3.0%
정귀완4
 
2.4%
조창호1
 
0.6%

논문명
Categorical

HIGH CARDINALITY

Distinct150
Distinct (%)91.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Neuraminidase Inhibitors from the Fruiting Body of Phellinus igniarius
 
3
Efficacy of HVT-IBD vector vaccine compared to attenuated live vaccine using in-ovo vaccination against a Korean very virulent IBDV in commercial broiler chickens
 
3
Attuning hydroxypropyl methylcellulose phthalate to oral delivery vehicle for effective and selective delivery of protein vaccine in ileum
 
2
Prevalence and antimicrobial resistance of Campylobacter spp. isolated from retail chicken and duck meat in South Korea
 
2
Effects of various LED light colors on growth and immune response in broilers
 
2
Other values (145)
152 

Length

Max length200
Median length142.5
Mean length111.1890244
Min length33

Unique

Unique138 ?
Unique (%)84.1%

Sample

1st rowChylous ascites in a hedgehog (Atelerix Albiventris)
2nd row다양한 PRRSV 감염상태에 있는 돼지 혈청을 이용한 PRRS 항체 ELISA 키트들의 비교 평가
3rd rowPrimary pheochromocytoma in an Asian Water Buffalo (Bubalus bubalis)
4th rowAsymmetrical ocular dermoid in native korean cattle
5th row국내 분리 부종병 대장균의 병원성 유전자 및 시가독소 생성 검증

Common Values

ValueCountFrequency (%)
Neuraminidase Inhibitors from the Fruiting Body of Phellinus igniarius3
 
1.8%
Efficacy of HVT-IBD vector vaccine compared to attenuated live vaccine using in-ovo vaccination against a Korean very virulent IBDV in commercial broiler chickens3
 
1.8%
Attuning hydroxypropyl methylcellulose phthalate to oral delivery vehicle for effective and selective delivery of protein vaccine in ileum2
 
1.2%
Prevalence and antimicrobial resistance of Campylobacter spp. isolated from retail chicken and duck meat in South Korea2
 
1.2%
Effects of various LED light colors on growth and immune response in broilers2
 
1.2%
Soluble RANKL expression in Lactococcus lactis and investigation for its potential as an oral vaccine adjuvant2
 
1.2%
Phenotypic Markers for Tetraploid Watermelon [Citrullus lanatus (Thunb.) Matsum. et Nakai] Following Parental Exposure to Colchicine in T0 Generation2
 
1.2%
Poultry vaccination directed evolution of H9N2 low pathogenicity avian influenza viruses in Korea2
 
1.2%
Microneedle Vaccination Elicits Superior Protection and Antibody Response over Intranasal Vaccination against Swine-Origin Influenza A (H1N1) in Mice2
 
1.2%
Development of the novel coating formulations for skin vaccination using stainless steel microneedle2
 
1.2%
Other values (140)142
86.6%

Length

2022-08-12T23:49:11.031535image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
of161
 
6.6%
and85
 
3.5%
in83
 
3.4%
a54
 
2.2%
the41
 
1.7%
porcine34
 
1.4%
for32
 
1.3%
virus27
 
1.1%
from26
 
1.1%
with23
 
0.9%
Other values (919)1868
76.7%

학술지 출판년도
Real number (ℝ≥0)

Distinct8
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2014.835366
Minimum2010
Maximum2017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2022-08-12T23:49:11.230980image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum2010
5-th percentile2012
Q12014
median2015
Q32016
95-th percentile2017
Maximum2017
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.441188326
Coefficient of variation (CV)0.0007152883807
Kurtosis0.1673933728
Mean2014.835366
Median Absolute Deviation (MAD)1
Skewness-0.7532715506
Sum330433
Variance2.077023792
MonotonicityNot monotonic
2022-08-12T23:49:11.384998image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
201654
32.9%
201539
23.8%
201430
18.3%
201316
 
9.8%
201712
 
7.3%
201210
 
6.1%
20112
 
1.2%
20101
 
0.6%
ValueCountFrequency (%)
20101
 
0.6%
20112
 
1.2%
201210
 
6.1%
201316
 
9.8%
201430
18.3%
201539
23.8%
201654
32.9%
201712
 
7.3%
ValueCountFrequency (%)
201712
 
7.3%
201654
32.9%
201539
23.8%
201430
18.3%
201316
 
9.8%
201210
 
6.1%
20112
 
1.2%
20101
 
0.6%

저자
Categorical

HIGH CARDINALITY
MISSING

Distinct125
Distinct (%)77.6%
Missing3
Missing (%)1.8%
Memory size1.4 KiB
김은미
 
5
Saadeldin IM
 
4
SungJun Hong
 
3
서병주
 
3
Hye Ran Park
 
3
Other values (120)
143 

Length

Max length38
Median length24
Mean length8.664596273
Min length3

Unique

Unique99 ?
Unique (%)61.5%

Sample

1st row노윤석
2nd row서병주;
3rd rowKim, WonIl;
4th row노윤석
5th row서병주

Common Values

ValueCountFrequency (%)
김은미5
 
3.0%
Saadeldin IM4
 
2.4%
SungJun Hong3
 
1.8%
서병주3
 
1.8%
Hye Ran Park3
 
1.8%
김희정3
 
1.8%
Byung Soon Hwang3
 
1.8%
Park HR2
 
1.2%
Surim Park2
 
1.2%
JinYong Noh2
 
1.2%
Other values (115)131
79.9%
(Missing)3
 
1.8%

Length

2022-08-12T23:49:11.595661image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
park19
 
6.3%
kim14
 
4.7%
lee8
 
2.7%
김은미5
 
1.7%
im5
 
1.7%
hong5
 
1.7%
kang5
 
1.7%
saadeldin4
 
1.3%
shin4
 
1.3%
hwang4
 
1.3%
Other values (159)228
75.7%

학술지명
Categorical

HIGH CARDINALITY

Distinct108
Distinct (%)65.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
한국가축위생학회지
 
9
Mycobiology
 
5
韓國家畜衛生學會誌 = Korean journal of veterinary service
 
4
Poultry science
 
4
Archives of Virology
 
4
Other values (103)
138 

Length

Max length62
Median length38
Mean length22.38414634
Min length6

Unique

Unique74 ?
Unique (%)45.1%

Sample

1st rowJournal of Zoo and Wildlife Medicine
2nd row韓國家畜衛生學會誌 = Korean journal of veterinary service
3rd row韓國家畜衛生學會誌 = Korean journal of veterinary service
4th rowThe Journal of Animal & Plant Sciences
5th rowKorean journal of veterinary service

Common Values

ValueCountFrequency (%)
한국가축위생학회지9
 
5.5%
Mycobiology5
 
3.0%
韓國家畜衛生學會誌 = Korean journal of veterinary service4
 
2.4%
Poultry science4
 
2.4%
Archives of Virology4
 
2.4%
PLos One3
 
1.8%
Journal of Animal and Veterinary Advances3
 
1.8%
Veterinary Immunology and Immunopathology3
 
1.8%
Experimental Neurobiology3
 
1.8%
Theriogenology3
 
1.8%
Other values (98)123
75.0%

Length

2022-08-12T23:49:11.806781image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
of47
 
9.5%
journal44
 
8.9%
veterinary25
 
5.1%
science16
 
3.2%
and16
 
3.2%
korean14
 
2.8%
j11
 
2.2%
10
 
2.0%
한국가축위생학회지9
 
1.8%
virology8
 
1.6%
Other values (133)294
59.5%

Interactions

2022-08-12T23:49:07.440967image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-08-12T23:49:05.904584image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-08-12T23:49:06.756993image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-08-12T23:49:07.602271image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-08-12T23:49:06.186000image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-08-12T23:49:06.986387image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-08-12T23:49:07.796949image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-08-12T23:49:06.550967image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2022-08-12T23:49:07.205542image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Correlations

2022-08-12T23:49:11.962202image/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.
2022-08-12T23:49:12.262142image/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.
2022-08-12T23:49:12.454992image/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.
2022-08-12T23:49:12.664310image/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.
2022-08-12T23:49:12.859744image/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

2022-08-12T23:49:08.127598image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
A simple visualization of nullity by column.
2022-08-12T23:49:08.452104image/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.
2022-08-12T23:49:08.605011image/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
01수의112131병원체 특이 박테리오파지를 이용한 돼지 세균성 병원체 제어제 개발김원일Chylous ascites in a hedgehog (Atelerix Albiventris)2014노윤석Journal of Zoo and Wildlife Medicine
12수의112131병원체 특이 박테리오파지를 이용한 돼지 세균성 병원체 제어제 개발김원일다양한 PRRSV 감염상태에 있는 돼지 혈청을 이용한 PRRS 항체 ELISA 키트들의 비교 평가2014서병주;韓國家畜衛生學會誌 = Korean journal of veterinary service
23수의112131병원체 특이 박테리오파지를 이용한 돼지 세균성 병원체 제어제 개발김원일Primary pheochromocytoma in an Asian Water Buffalo (Bubalus bubalis)2013Kim, WonIl;韓國家畜衛生學會誌 = Korean journal of veterinary service
34수의112131병원체 특이 박테리오파지를 이용한 돼지 세균성 병원체 제어제 개발김원일Asymmetrical ocular dermoid in native korean cattle2014노윤석The Journal of Animal & Plant Sciences
45수의112131병원체 특이 박테리오파지를 이용한 돼지 세균성 병원체 제어제 개발김원일국내 분리 부종병 대장균의 병원성 유전자 및 시가독소 생성 검증2016서병주Korean journal of veterinary service
56수의112131병원체 특이 박테리오파지를 이용한 돼지 세균성 병원체 제어제 개발김원일하절기 급사 돼지의 Clostridium novyi 진단 및 분리2016정창기한국가축위생학회지
67수의112131병원체 특이 박테리오파지를 이용한 돼지 세균성 병원체 제어제 개발김원일Primary B cell lymphoma of submandibular lymph node in a water deer (Hydropotes inermis)2016Surim ParkJournal of Wildlife Disease
78수의112131병원체 특이 박테리오파지를 이용한 돼지 세균성 병원체 제어제 개발김원일국내 분리 돼지 부종병 대장균의 병원성 유전자 및 시가독소 생성 검증2016서병주한국가축위생학회지
89수의112131병원체 특이 박테리오파지를 이용한 돼지 세균성 병원체 제어제 개발김원일Co-infection with Hepatozoon sp. and canine distember virus in yellow-throated marten (Martes flavigula koreana)2016Surim ParkJournal of Wildlife Diseases
910수의115099축종(오리,육계,토종닭 등) 최적 소독 및 방역관리 모델 개발조창호Isolation and genomic characterization of a novel avian orthoreovirus in Korea, 20142017JinYong NohAvian disease

Last rows

번호분류과제번호과제명연구책임자논문명학술지 출판년도저자학술지명
154155수의313016국내분리 H5N1형 HPAI의 주요 야생조류 종별 병원성 및 병리기전 구명김재홍Pathogenicity of the Korean H5N8 highly pathogenic avian influenza virus in commercial2016DongHun Leeavian pathology
155156수의313016국내분리 H5N1형 HPAI의 주요 야생조류 종별 병원성 및 병리기전 구명김재홍Experimental Infection of Chickens with Intercontinental Reassortant H9N2 Influenza Viruses from Wild Birds2016권정훈Avian diseases
156157수의313016국내분리 H5N1형 HPAI의 주요 야생조류 종별 병원성 및 병리기전 구명김재홍Highly Pathogenic Avian Influenza A(H5N8) viruses reintroduced into South Korea by migratory2016권정훈Emerging Infectious Diseases
157158수의313060다축종 (산업동물 및 반려동물 포함) 적용 가능한 신속, 정확한 인플루엔자 검출 기법 개발 및 상용화박현규Single-Step Real-Time Reverse Transcription-Polymerase Chain Reaction for Simultaneous Detection of H5N1 and H5N8 Highly Pathogenic Avian Influenza Viruses2015김은미Journal of Animal and Veterinary Advances
158159수의313060다축종 (산업동물 및 반려동물 포함) 적용 가능한 신속, 정확한 인플루엔자 검출 기법 개발 및 상용화박현규DNA 교차 오염 방지 기능을 가진 돼지 인플루엔자바이러스 감별진단용 one-step multiplex RT-PCR 진단법2014김희정한국가축위생학회지
159160수의313060다축종 (산업동물 및 반려동물 포함) 적용 가능한 신속, 정확한 인플루엔자 검출 기법 개발 및 상용화박현규국내 양돈장의 사육구간별 주요 소화기질병 원인체 유병율 조사2016정윤수Korean Journal of Veterinary Service
160161수의313060다축종 (산업동물 및 반려동물 포함) 적용 가능한 신속, 정확한 인플루엔자 검출 기법 개발 및 상용화박현규Evaluation of Reverse-Transcription Loop-Mediated Isothermal Amplification Assay For Screening Influenza A Viruses From Different Animal Species2015김은미Journal of Animal and Veterinary Advances
161162수의313060다축종 (산업동물 및 반려동물 포함) 적용 가능한 신속, 정확한 인플루엔자 검출 기법 개발 및 상용화박현규Molecular analysis of the hexon, penton base, and fiber-2 genes of Korean fowl adenovirus serotype 4 isolates from hydropericardium syndrome-affected chickens2017박현규Virus Genes
162163수의313060다축종 (산업동물 및 반려동물 포함) 적용 가능한 신속, 정확한 인플루엔자 검출 기법 개발 및 상용화박현규UNG 기반 direct polymerase chain reaction (udPCR)을 이용한 돼지 써코바이러스 2형 진단번2014김은미한국가축위생학회지
163164수의313060다축종 (산업동물 및 반려동물 포함) 적용 가능한 신속, 정확한 인플루엔자 검출 기법 개발 및 상용화박현규Uracil-DNA glycosylase-treated reverse transcription loop-mediated isothermal amplification for rapid detection of avian influenza virus preventing carry-over contamination2016김은미JOURNAL OF VETERINARY SCIENCE