Automated Author ProfileMehede H. Rubel
Mehede H. Rubel
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 2.5 (sum of 3 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Various pathovars (pv.) of Xanthomonas campestris (Xc) are prevalent in South Korea, of which pv. campestris causing black rot threatens the production of cabbage in this major cabbage producing country of the world. Rapid and sensitive detection of the pathovar is an essential prerequisite for any plant protection programme. This study took an approach of re-aligning the whole genome sequences (upon availability) of representative strains of the bacteria and identified pathovar-specific genomic regions that are absent in other pathovars and other bacterial strains. Herein, eight Sequence Characterized Amplified Regions (SCAR) primer sets were designed, of which three sets, namely Xcc_48F/R, Xcc_53F/R and Xcc_79F/R, specifically amplified all Xcc strains and did not amplify other pathovars and bacterial strains. These primers also detected the Xcc strains collected from black rot infected field samples in South Korea. After optimizing the PCR conditions, one of the primers, Xcc_48F/R, was able to amplify as low as 6 × 10−3 ng μL−1 bacterial DNA. This unique method of marker development thus yielded sensitive, specific and reliable markers that can be used for efficient and inexpensive detection of Xcc for purposes including quarantine and disease forecasting by early detection from asymptomatic field samples. Additionally, the method can be replicated in developing markers from other phyto-pathogenic agents for which the variable genomic regions are not known.
Authors
- Mehede H. Rubel ;
- MEHEDE H. RUBEL ;
- Sathishkumar Natarajan ;
- SATHISHKUMAR NATARAJAN ;
- Hossain, Mohammad R. ;
- MOHAMMAD R. HOSSAIN ;
- Nath, Ujjal K. ;
- UJJAL K. NATH ;
- Khandker S. Afrin ;
- KHANDKER S. AFRIN ;
- Lee, Ji-Hee ;
- JI-HEE LEE ;
- Jung, Hee-Jeong ;
- HEE-JEONG JUNG ;
- Hoy-Taek Kim ;
- HOY-TAEK KIM ;
- Park, Jong-In ;
- JONG-IN PARK ;
- Ill-Sup Nou ;
- ILL-SUP NOU
Various pathovars (pv.) of Xanthomonas campestris (Xc) are prevalent in South Korea, of which pv. campestris causing black rot threatens the production of cabbage in this major cabbage producing country of the world. Rapid and sensitive detection of the pathovar is an essential prerequisite for any plant protection programme. This study took an approach of re-aligning the whole genome sequences (upon availability) of representative strains of the bacteria and identified pathovar-specific genomic regions that are absent in other pathovars and other bacterial strains. Herein, eight Sequence Characterized Amplified Regions (SCAR) primer sets were designed, of which three sets, namely Xcc_48F/R, Xcc_53F/R and Xcc_79F/R, specifically amplified all Xcc strains and did not amplify other pathovars and bacterial strains. These primers also detected the Xcc strains collected from black rot infected field samples in South Korea. After optimizing the PCR conditions, one of the primers, Xcc_48F/R, was able to amplify as low as 6 × 10−3 ng μL−1 bacterial DNA. This unique method of marker development thus yielded sensitive, specific and reliable markers that can be used for efficient and inexpensive detection of Xcc for purposes including quarantine and disease forecasting by early detection from asymptomatic field samples. Additionally, the method can be replicated in developing markers from other phyto-pathogenic agents for which the variable genomic regions are not known.
Authors
- Mehede H. Rubel ;
- Sathishkumar Natarajan ;
- Hossain, Mohammad R. ;
- Nath, Ujjal K. ;
- Khandker S. Afrin ;
- Lee, Ji-Hee ;
- Jung, Hee-Jeong ;
- Hoy-Taek Kim ;
- Park, Jong-In ;
- Ill-Sup Nou
Various pathovars (pv.) of Xanthomonas campestris (Xc) are prevalent in South Korea, of which pv. campestris causing black rot threatens the production of cabbage in this major cabbage producing country of the world. Rapid and sensitive detection of the pathovar is an essential prerequisite for any plant protection programme. This study took an approach of re-aligning the whole genome sequences (upon availability) of representative strains of the bacteria and identified pathovar-specific genomic regions that are absent in other pathovars and other bacterial strains. Herein, eight Sequence Characterized Amplified Regions (SCAR) primer sets were designed, of which three sets, namely Xcc_48F/R, Xcc_53F/R and Xcc_79F/R, specifically amplified all Xcc strains and did not amplify other pathovars and bacterial strains. These primers also detected the Xcc strains collected from black rot infected field samples in South Korea. After optimizing the PCR conditions, one of the primers, Xcc_48F/R, was able to amplify as low as 6 × 10−3 ng μL−1 bacterial DNA. This unique method of marker development thus yielded sensitive, specific and reliable markers that can be used for efficient and inexpensive detection of Xcc for purposes including quarantine and disease forecasting by early detection from asymptomatic field samples. Additionally, the method can be replicated in developing markers from other phyto-pathogenic agents for which the variable genomic regions are not known.
Authors
- Mehede H. Rubel ;
- MEHEDE H. RUBEL ;
- Sathishkumar Natarajan ;
- SATHISHKUMAR NATARAJAN ;
- Hossain, Mohammad R. ;
- MOHAMMAD R. HOSSAIN ;
- Nath, Ujjal K. ;
- UJJAL K. NATH ;
- Khandker S. Afrin ;
- KHANDKER S. AFRIN ;
- Lee, Ji-Hee ;
- JI-HEE LEE ;
- Jung, Hee-Jeong ;
- HEE-JEONG JUNG ;
- Hoy-Taek Kim ;
- HOY-TAEK KIM ;
- Park, Jong-In ;
- JONG-IN PARK ;
- Ill-Sup Nou ;
- ILL-SUP NOU