Most recent issue published online in the International Journal of Computational Biology and Drug Design.
International Journal of Computational Biology and Drug Design
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International Journal of Computational Biology and Drug Design
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http://www.inderscience.com/browse/index.php?journalID=294&year=2023&vol=15&issue=6
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Genetic variability, correlation, diversity, path coefficients and principal component analysis in Indian mustard
http://www.inderscience.com/link.php?id=134613
After soybean and palm, Brassica species are the third-most significant oilseed crops in the world. Globally, Indian mustard (<i>Brassica juncea</i> L.) is used as an oilseed, a vegetable, and a condiment. The 70 different genotypes of Indian mustard were grown at the farm of Visva-Bharati University's Institute of Agriculture using an RCBD with three replications in 2017-2018 and 2018-2019 to investigate genetic variability, cause and effect relationship and diversity. The findings demonstrated that environmental factors contribute to the development of characteristics because the PCV values were higher than the GCV values. The direct impact of seed yield per plant on oil production per plant was highly positive (0.551). Using Tocher's technique, the 70 genotypes were divided into eight groups. The mustard accessions' PCA revealed a varied pattern of grouping. The main genetic factors that caused genetic divergence were the oil yield per plant, seed yield per plant, number of siliqua on branches and number of siliqua per plant.
Genetic variability, correlation, diversity, path coefficients and principal component analysis in Indian mustard
Sumanta Prasad Chand; Sandip Debnath; Mehdi Rahimi; Shampa Purakayastha; Sanghamitra Rout
International Journal of Computational Biology and Drug Design, Vol. 15, No. 6 (2023) pp. 445 - 462
After soybean and palm, Brassica species are the third-most significant oilseed crops in the world. Globally, Indian mustard (<i>Brassica juncea</i> L.) is used as an oilseed, a vegetable, and a condiment. The 70 different genotypes of Indian mustard were grown at the farm of Visva-Bharati University's Institute of Agriculture using an RCBD with three replications in 2017-2018 and 2018-2019 to investigate genetic variability, cause and effect relationship and diversity. The findings demonstrated that environmental factors contribute to the development of characteristics because the PCV values were higher than the GCV values. The direct impact of seed yield per plant on oil production per plant was highly positive (0.551). Using Tocher's technique, the 70 genotypes were divided into eight groups. The mustard accessions' PCA revealed a varied pattern of grouping. The main genetic factors that caused genetic divergence were the oil yield per plant, seed yield per plant, number of siliqua on branches and number of siliqua per plant.]]>
10.1504/IJCBDD.2023.134613
International Journal of Computational Biology and Drug Design, Vol. 15, No. 6 (2023) pp. 445 - 462
Sumanta Prasad Chand
Sandip Debnath
Mehdi Rahimi
Shampa Purakayastha
Sanghamitra Rout
Department of Genetics and Plant Breeding, Institute of Agriculture, Visva-Bharati University, Sriniketan, West Bengal, 731236, India ' Department of Genetics and Plant Breeding, Institute of Agriculture, Visva-Bharati University, Sriniketan, West Bengal, 731236, India ' Department of Biotechnology, Institute of Science and High Technology and Environmental Sciences, Graduate University of Advanced Technology, Kerman, 7631885356, Iran ' Department of Genetics and Plant Breeding and Seed Science and Technology, Centurion University of Technology and Management, Paralekhamumdi, Gajapati, Odisha, 761211, India ' Department of Genetics and Plant Breeding and Seed Science and Technology, Centurion University of Technology and Management, Paralekhamumdi, Gajapati, Odisha, 761211, India
Brassica juncea
cluster
variance
path
Tocher's method
Mahalanobis D2 statistic
principal component analysis
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Copyright © 2023 Inderscience Enterprises Ltd.
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Assessment and validation of emulgel-based salicylic acid formulation development for drug release and optimisation by statistical design
http://www.inderscience.com/link.php?id=134615
Salicylic acid is used topically to treat a variety of skin problems, such as acne, dandruff, psoriasis, seborrheic dermatitis, calluses, corns and warts. The effects of Methocel K100 LV, Cetostearyl alcohol and Span80 independent variables on the drug release of emulgel utilised to create design expert software. The formulations of three underwent testing for physical characteristics, spreadability, washability, skin irritability, agar plate diffusion and drug release. When comparing S7 to the commercial product (Salicylix SF12), a considerable contribution was discovered. The design expert was utilised to determine the effects of the three aspects individually and collectively. There was a significant as indicated by the analysis of variance results (p < 0.05). The formulation variables need to be controlled to produce an emulgel with the necessary performance qualities. The predictability and validity of the model were demonstrated when the experimental results matched the predicted values.
Assessment and validation of emulgel-based salicylic acid formulation development for drug release and optimisation by statistical design
Ch. Taraka Ramarao; Ishwarya Bammidi; Manasa Banala; Kundansai Balaga; Pavani Cheekati; Yamani Busa
International Journal of Computational Biology and Drug Design, Vol. 15, No. 6 (2023) pp. 463 - 479
Salicylic acid is used topically to treat a variety of skin problems, such as acne, dandruff, psoriasis, seborrheic dermatitis, calluses, corns and warts. The effects of Methocel K100 LV, Cetostearyl alcohol and Span80 independent variables on the drug release of emulgel utilised to create design expert software. The formulations of three underwent testing for physical characteristics, spreadability, washability, skin irritability, agar plate diffusion and drug release. When comparing S7 to the commercial product (Salicylix SF12), a considerable contribution was discovered. The design expert was utilised to determine the effects of the three aspects individually and collectively. There was a significant as indicated by the analysis of variance results (p < 0.05). The formulation variables need to be controlled to produce an emulgel with the necessary performance qualities. The predictability and validity of the model were demonstrated when the experimental results matched the predicted values.]]>
10.1504/IJCBDD.2023.134615
International Journal of Computational Biology and Drug Design, Vol. 15, No. 6 (2023) pp. 463 - 479
Ch. Taraka Ramarao
Ishwarya Bammidi
Manasa Banala
Kundansai Balaga
Pavani Cheekati
Yamani Busa
Department of Pharmaceutics, Sri Venkateswara College of Pharmacy, Etchrela, Srikakulam, Andhra Pradesh, 532410, India ' Department of Pharmaceutics, Sri Venkateswara College of Pharmacy, Etchrela, Srikakulam, Andhra Pradesh, 532410, India ' Department of Pharmaceutics, Sri Venkateswara College of Pharmacy, Etchrela, Srikakulam, Andhra Pradesh, 532410, India ' Department of Pharmaceutics, Sri Venkateswara College of Pharmacy, Etchrela, Srikakulam, Andhra Pradesh, 532410, India ' Department of Pharmaceutics, Sri Venkateswara College of Pharmacy, Etchrela, Srikakulam, Andhra Pradesh, 532410, India ' Department of Pharmaceutics, Sri Venkateswara College of Pharmacy, Etchrela, Srikakulam, Andhra Pradesh, 532410, India
emulgel
Salicylix SF12
ex vivo
agar plate diffusion
design expert
2023-10-31T23:20:50-05:00
Copyright © 2023 Inderscience Enterprises Ltd.
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479
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EyeRIS: image-based identification of goats using Iris
http://www.inderscience.com/link.php?id=134616
Existing identification systems for goats are physically tamperable and thus a biometric system needs to be developed to overcome such. After image acquisition through single lens reflex (SLR) camera, the iris potion is segmented using snake contouring, normalised and feature encoded leading to the generation of templates. The matching between such stored and query templates using the metric of hamming distance develops a specific threshold, wherein the values less than it claim to be of the same individual and vice versa for different individual goats. During this experimentation, the recognition of black Bengal goats using iris patterns has been established as a unique and viable trait. Later, it has been extrapolated to the other five breeds named Jamunapuri, Sirohi, Beetal, Jakhrana, and Barbari. The accuracy has been found to be 98%, better than that of different technologies for identification of animals, keeping the time complexity under prime consideration.
EyeRIS: image-based identification of goats using Iris
Satyendra Nath Mandal; Subhranil Mustafi; Sanket Dan; Pritam Ghosh; Dilip Kumar Hajra; Santanu Banik; Shyamal Naskar
International Journal of Computational Biology and Drug Design, Vol. 15, No. 6 (2023) pp. 480 - 502
Existing identification systems for goats are physically tamperable and thus a biometric system needs to be developed to overcome such. After image acquisition through single lens reflex (SLR) camera, the iris potion is segmented using snake contouring, normalised and feature encoded leading to the generation of templates. The matching between such stored and query templates using the metric of hamming distance develops a specific threshold, wherein the values less than it claim to be of the same individual and vice versa for different individual goats. During this experimentation, the recognition of black Bengal goats using iris patterns has been established as a unique and viable trait. Later, it has been extrapolated to the other five breeds named Jamunapuri, Sirohi, Beetal, Jakhrana, and Barbari. The accuracy has been found to be 98%, better than that of different technologies for identification of animals, keeping the time complexity under prime consideration.]]>
10.1504/IJCBDD.2023.134616
International Journal of Computational Biology and Drug Design, Vol. 15, No. 6 (2023) pp. 480 - 502
Satyendra Nath Mandal
Subhranil Mustafi
Sanket Dan
Pritam Ghosh
Dilip Kumar Hajra
Santanu Banik
Shyamal Naskar
Department of Information Technology, Kalyani Government Engineering College, Kalyani, Nadia, West Bengal, 741235, India ' DST-INSPIRE Fellow, CVPR Unit, Indian Statistical Institute, Kolkata, West Bengal 700108, India ' Department of Information Technology, Kalyani Government Engineering College, Kalyani, Nadia, West Bengal, 741235, India ' Department of Computer Science & Technology, Iswar Chandra Vidyasagar Polytechnic, Jhargram, West Bengal, 721514, India ' Department of Agronomy, Uttar Banga Krishi Vishwavidyalaya, Pundibari, West Bengal, 736165, India ' Principal Scientist (Animal Genetics and Breeding), ICAR-National Research Centre on Pig, Rani, Assam, 781015, India ' ICAR †Indian Veterinary Research Institute, Kolkata, West Bengal, 700037, India
goat Aadhaar
log Gabor filter
convolution
template generation
hamming distance
2023-10-31T23:20:50-05:00
Copyright © 2023 Inderscience Enterprises Ltd.
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SMLBT: secure machine learning and blockchain-based telemedicine model for the remote areas of developing countries
http://www.inderscience.com/link.php?id=134617
A reliable data safety model is currently an urgent demand for the healthcare system across the world, especially for people dwelling in rural areas, and this domain requires top-notch security. Telemedicine services can serve rural communities with appropriate medical guidance, but patient data security is still in question. In this work, we propose a telemedicine system using blockchain technology that can ensure the data security of patients from remote and rustic regions of any country. Based on the literature, we present a medical information system, which includes data pre-processing and cleaning. To create prediction models, we propose supervised and unsupervised machine learning (ML) technologies to analyse patient narratives and electronic medical records (EMR). These ML approaches will initiate early diagnostics to transform the system into a more scalable format. Furthermore, this model may put forward economic, social, and technologically enhanced medical advantages to the citizens of rural areas.
SMLBT: secure machine learning and blockchain-based telemedicine model for the remote areas of developing countries
Milon Biswas; Atanu Shome; Prodipta Promit Mukherjee; Loveleen Gaur; Zhongming Zhao
International Journal of Computational Biology and Drug Design, Vol. 15, No. 6 (2023) pp. 503 - 517
A reliable data safety model is currently an urgent demand for the healthcare system across the world, especially for people dwelling in rural areas, and this domain requires top-notch security. Telemedicine services can serve rural communities with appropriate medical guidance, but patient data security is still in question. In this work, we propose a telemedicine system using blockchain technology that can ensure the data security of patients from remote and rustic regions of any country. Based on the literature, we present a medical information system, which includes data pre-processing and cleaning. To create prediction models, we propose supervised and unsupervised machine learning (ML) technologies to analyse patient narratives and electronic medical records (EMR). These ML approaches will initiate early diagnostics to transform the system into a more scalable format. Furthermore, this model may put forward economic, social, and technologically enhanced medical advantages to the citizens of rural areas.]]>
10.1504/IJCBDD.2023.134617
International Journal of Computational Biology and Drug Design, Vol. 15, No. 6 (2023) pp. 503 - 517
Milon Biswas
Atanu Shome
Prodipta Promit Mukherjee
Loveleen Gaur
Zhongming Zhao
Department of Computer Science, University of Alabama, Birmingham, AL 35294, USA ' Department of Computer Science, Khulna University, Khulna-9208, Bangladesh ' Research and Development Department, zBack Systems Limited, Mirpur DOHS, Dhaka-1216, Bangladesh ' Amity International Business School, Amity University, Noida-201313, India ' Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
telemedicine
blockchain
security
data safety
machine learning
prediction
2023-10-31T23:20:50-05:00
Copyright © 2023 Inderscience Enterprises Ltd.
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517
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Simulate the agarose gel of the receptor binding domain in Omicron's spike protein inserted into the pGEM®-T Easy vector using SpeI and SacI restriction enzymes
http://www.inderscience.com/link.php?id=134614
The Omicron variant of SARS-CoV-2 spreads swiftly among humans because of the mutations it carries. <i>Aim</i>: The goal of this study was to find a full design of the polymerase chain reaction (PCR) protocol for determining SARS-CoV-2 using <i>In silico</i> tools. The receptor-binding domain (RBD) of the spike protein is a crucial component. <i>Materials and Methods</i>: RBD interacts with ACE2 receptors on the surface of respiratory lining cells. The linear RBD was inserted into the supercoiled pGEM®-T Easy vector using <i>SpeI</i> and <i>SacI</i> restriction enzymes. The RBD was amplified to perform the conventional PCR technique after designing specific primers. <i>Results</i>: The (pGEM®-T Easy-RBD Mut.) clone was created by inserting the Omicron RBD gene into a supercoiled pGEM®-T Easy commercial vector. The results were predicted using gel electrophoresis. Even though the classic PCR method takes time due to the electrophoresis procedure, it is a very efficient tool for detecting novel strains.
Simulate the agarose gel of the receptor binding domain in Omicron's spike protein inserted into the pGEM®-T Easy vector using SpeI and SacI restriction enzymes
Ali Adel Dawood
International Journal of Computational Biology and Drug Design, Vol. 15, No. 6 (2023) pp. 518 - 526
The Omicron variant of SARS-CoV-2 spreads swiftly among humans because of the mutations it carries. <i>Aim</i>: The goal of this study was to find a full design of the polymerase chain reaction (PCR) protocol for determining SARS-CoV-2 using <i>In silico</i> tools. The receptor-binding domain (RBD) of the spike protein is a crucial component. <i>Materials and Methods</i>: RBD interacts with ACE2 receptors on the surface of respiratory lining cells. The linear RBD was inserted into the supercoiled pGEM®-T Easy vector using <i>SpeI</i> and <i>SacI</i> restriction enzymes. The RBD was amplified to perform the conventional PCR technique after designing specific primers. <i>Results</i>: The (pGEM®-T Easy-RBD Mut.) clone was created by inserting the Omicron RBD gene into a supercoiled pGEM®-T Easy commercial vector. The results were predicted using gel electrophoresis. Even though the classic PCR method takes time due to the electrophoresis procedure, it is a very efficient tool for detecting novel strains.]]>
10.1504/IJCBDD.2023.134614
International Journal of Computational Biology and Drug Design, Vol. 15, No. 6 (2023) pp. 518 - 526
Milon Biswas
Atanu Shome
Prodipta Promit Mukherjee
Loveleen Gaur
Zhongming Zhao
Department of Anatomy, College of Medicine, University of Mosul, Mosul, 00964, Iraq
Omicron
SARS-CoV-2
vector
RBD
receptor-binding domain
spike
2023-10-31T23:20:50-05:00
Copyright © 2023 Inderscience Enterprises Ltd.
15
6
518
526
2023-10-31T23:20:50-05:00