Catalogue de la bibliothèque de SNV
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570.285 : Informatique appliquée à la biologie et aux sciences de la vie - bio-informatique - 570 Biologie générale, (sciences de la vie ) 570.03 Dictionnaire de biologie 570.1 Philosophie et théorie de la biologie et des sciences de la vie 570.15 Principes scientifiques de la biologie et des sciences de la vie 570.151 95 Biostatistique ( biométrie ) 570.2 Ouvrages divers en relation avec la biologie et les sciences de la vie 570.282 Microscopie en biologie 570.3 570.7 Biologie : Enseignement |
Ouvrages de la bibliothèque en indexation 570.285
Affiner la rechercheBioinformatics / Jeremy J. Ramsden / Londres : Springer (2023)
Titre : Bioinformatics : An introduction Type de document : texte imprimé Auteurs : Jeremy J. Ramsden, Auteur Mention d'édition : Fourth edition Editeur : Londres : Springer Année de publication : 2023 Importance : 1 vol. (XXII-404 p.) Présentation : ill., couv. ill. Format : 24 cm ISBN/ISSN/EAN : 978-3-030-45606-1 Langues : Anglais Catégories : Bio-informatique - Biostatistiques - Biomathématique - Mathématique - Informatique Mots-clés : Bio-informatique Biologie informatique Index. décimale : 570.285 Informatique appliquée à la biologie et aux sciences de la vie - bio-informatique - Résumé :
This invaluable textbook presents a self-contained introduction to the field of bioinformatics. Providing a comprehensive breadth of coverage while remaining accessibly concise, the text promotes a deep understanding of the field, supported by basic mathematical concepts, an emphasis on biological knowledge, and a holistic approach that highlights the connections unifying bioinformatics with other areas of science.
The thoroughly revised and enhanced fourth edition features new chapters focusing on regulation and control networks, the origins of life, evolution, statistics and causation, viruses, the microbiome, single cell analysis, drug discovery and forensic applications. This edition additionally includes new and updated material on the ontology of bioinformatics, data mining, ecosystems, and phenomics. Also covered are new developments in sequencing technologies, gene editing methods, and modelling of the brain, as well as state-of-the-art medical applications. Of specialtopicality is a new chapter on bioinformatics aspects of the coronavirus pandemic.
Topics and features:
Explains the fundamentals of set theory, combinatorics, probability, likelihood, causality, clustering, pattern recognition, randomness, complexity, systems, and networks
Discusses topics on ontogeny, phylogeny, genome structure, and regulation, as well as aspects of molecular biology
Critically examines the most significant practical applications, offering detailed descriptions of both the experimental process and the analysis of the data
Provides a varied selection of problems throughout the book, to stimulate further thinking
Encourages further reading through the inclusion of an extensive bibliography
This classic textbook builds upon the successful formula of previous editions with coverage of the latest advances in this exciting and fast-moving field. With its interdisciplinary scope, this unique guide will prove to be an essential study companion to a broad audience of undergraduate and beginning graduate students, spanning computer scientists focusing on bioinformatics, students of the physical sciences seeking a helpful primer on biology, and biologists desiring to better understand the theory underlying important applications of information science in biology.Note de contenu :
Sommaire:
-1- Introduction
-2- Overview
-3- Information
-4- Biology
-5- Omics
-6- ApplicationsBioinformatics : An introduction [texte imprimé] / Jeremy J. Ramsden, Auteur . - Fourth edition . - Londres : Springer, 2023 . - 1 vol. (XXII-404 p.) : ill., couv. ill. ; 24 cm.
ISBN : 978-3-030-45606-1
Langues : Anglais
Catégories : Bio-informatique - Biostatistiques - Biomathématique - Mathématique - Informatique Mots-clés : Bio-informatique Biologie informatique Index. décimale : 570.285 Informatique appliquée à la biologie et aux sciences de la vie - bio-informatique - Résumé :
This invaluable textbook presents a self-contained introduction to the field of bioinformatics. Providing a comprehensive breadth of coverage while remaining accessibly concise, the text promotes a deep understanding of the field, supported by basic mathematical concepts, an emphasis on biological knowledge, and a holistic approach that highlights the connections unifying bioinformatics with other areas of science.
The thoroughly revised and enhanced fourth edition features new chapters focusing on regulation and control networks, the origins of life, evolution, statistics and causation, viruses, the microbiome, single cell analysis, drug discovery and forensic applications. This edition additionally includes new and updated material on the ontology of bioinformatics, data mining, ecosystems, and phenomics. Also covered are new developments in sequencing technologies, gene editing methods, and modelling of the brain, as well as state-of-the-art medical applications. Of specialtopicality is a new chapter on bioinformatics aspects of the coronavirus pandemic.
Topics and features:
Explains the fundamentals of set theory, combinatorics, probability, likelihood, causality, clustering, pattern recognition, randomness, complexity, systems, and networks
Discusses topics on ontogeny, phylogeny, genome structure, and regulation, as well as aspects of molecular biology
Critically examines the most significant practical applications, offering detailed descriptions of both the experimental process and the analysis of the data
Provides a varied selection of problems throughout the book, to stimulate further thinking
Encourages further reading through the inclusion of an extensive bibliography
This classic textbook builds upon the successful formula of previous editions with coverage of the latest advances in this exciting and fast-moving field. With its interdisciplinary scope, this unique guide will prove to be an essential study companion to a broad audience of undergraduate and beginning graduate students, spanning computer scientists focusing on bioinformatics, students of the physical sciences seeking a helpful primer on biology, and biologists desiring to better understand the theory underlying important applications of information science in biology.Note de contenu :
Sommaire:
-1- Introduction
-2- Overview
-3- Information
-4- Biology
-5- Omics
-6- ApplicationsExemplaires
Code-barres Cote Support Localisation Section Disponibilité FB/15737 SNV8/1816 Livre Bibliothèque SNV Englais Disponible FB/15738 SNV8/1816 Livre Bibliothèque SNV Englais Disponible Documents numériques
https://link.springer.com/book/10.1007/978-3-030-45607-8URL
Titre : Bioinformatics : A practical guide to NCBI databases and sequence alignments Type de document : texte imprimé Auteurs : Ismail D. Hamid ; National Center for Biotechnology Information (U.S. Mention d'édition : First edition. Editeur : London : CRC press Année de publication : 2022 Importance : 1 Vol.(456 p.) Présentation : ill.en coul Format : 28 cm ISBN/ISSN/EAN : 978-1-03-212369-1 Langues : Anglais Catégories : Bio-informatique - Biostatistiques - Biomathématique - Mathématique - Informatique Mots-clés : Bioinformatics Biotechnology Microbiology Databases Index. décimale : 570.285 Informatique appliquée à la biologie et aux sciences de la vie - bio-informatique - Résumé :
"Bioinformatics: A Practical Guide to NCBI Databases and Sequence Alignments provides the basics of bioinformatics and in-depth coverage of NCBI databases, sequence alignment, and NCBI Sequence Local Alignment Search Tool (BLAST). As bioinformatics has become essential for life sciences, the book has been written specifically to address the need of a large audience including undergraduates, graduates, researchers, healthcare professionals, and bioinformatics professors who need to use the NCBI databases, retrieve data from them, and use BLAST to find evolutionarily related sequences, sequence annotation, construction of phylogenetic tree, and the conservative domain of a protein, to name just a few. Technical details of alignment algorithms are explained with a minimum use of mathematical formulas and with graphical illustrations. This is the ideal textbook for bioinformatics courses taken by students of life sciences and for researchers wishing to develop their knowledge of bioinformatics to facilitate their own research"--Note de contenu :
Sommaire:
Chapter 1 - The Origin of Genomic Information
Chapter 2 - The Sources of Genomic Data
Chapter 3 - The NCBI Entrez Databases
Chapter 4 - NCBI Entrez E- Utilities and Applications
Chapter 5 - The Entrez Direct
Chapter 6 - R and Python Packages for the NCBI E- Utilities
Chapter 7 - Pairwise Sequence Alignment
Chapter 8 - Basic Local Alignment Search ToolBioinformatics : A practical guide to NCBI databases and sequence alignments [texte imprimé] / Ismail D. Hamid ; National Center for Biotechnology Information (U.S. . - First edition. . - London : CRC press, 2022 . - 1 Vol.(456 p.) : ill.en coul ; 28 cm.
ISBN : 978-1-03-212369-1
Langues : Anglais
Catégories : Bio-informatique - Biostatistiques - Biomathématique - Mathématique - Informatique Mots-clés : Bioinformatics Biotechnology Microbiology Databases Index. décimale : 570.285 Informatique appliquée à la biologie et aux sciences de la vie - bio-informatique - Résumé :
"Bioinformatics: A Practical Guide to NCBI Databases and Sequence Alignments provides the basics of bioinformatics and in-depth coverage of NCBI databases, sequence alignment, and NCBI Sequence Local Alignment Search Tool (BLAST). As bioinformatics has become essential for life sciences, the book has been written specifically to address the need of a large audience including undergraduates, graduates, researchers, healthcare professionals, and bioinformatics professors who need to use the NCBI databases, retrieve data from them, and use BLAST to find evolutionarily related sequences, sequence annotation, construction of phylogenetic tree, and the conservative domain of a protein, to name just a few. Technical details of alignment algorithms are explained with a minimum use of mathematical formulas and with graphical illustrations. This is the ideal textbook for bioinformatics courses taken by students of life sciences and for researchers wishing to develop their knowledge of bioinformatics to facilitate their own research"--Note de contenu :
Sommaire:
Chapter 1 - The Origin of Genomic Information
Chapter 2 - The Sources of Genomic Data
Chapter 3 - The NCBI Entrez Databases
Chapter 4 - NCBI Entrez E- Utilities and Applications
Chapter 5 - The Entrez Direct
Chapter 6 - R and Python Packages for the NCBI E- Utilities
Chapter 7 - Pairwise Sequence Alignment
Chapter 8 - Basic Local Alignment Search ToolExemplaires
Code-barres Cote Support Localisation Section Disponibilité FB/15611 SNV4/0486 Livre Bibliothèque SNV Englais Disponible FB/15610 SNV4/0486 Livre Bibliothèque SNV Englais Disponible
Titre : Bioinformatique : cours et applications Type de document : texte imprimé Auteurs : Gilbert Deléage (1956-...), Auteur ; Manolo Gouy (19..-....), Auteur Mention d'édition : 2 ed Editeur : Paris [France] : Dunod Année de publication : 2015 Collection : Sciences sup, ISSN 1636-2241 Importance : 1 vol. (XI-203 p.) Présentation : ill., graph., fig., tabl., couv. ill. en coul. Format : 24 cm ISBN/ISSN/EAN : 978-2-10-072752-0 Langues : Français Catégories : Bio-informatique - Biostatistiques - Biomathématique - Mathématique - Informatique Mots-clés : Bioinformatique Index. décimale : 570.285 Informatique appliquée à la biologie et aux sciences de la vie - bio-informatique - Résumé :
La bioinformatique est une "interdiscipline" à la frontière de la biologie, de l'informatique et des mathématiques. Elle a pour but d'intégrer des données d'origines très diverses pour modéliser les systèmes vivants afin de comprendre et prédire leurs comportements (analyse du génome, modélisation de l'évolution d'une population animale dans un environnement donné, modélisation moléculaire, reconstruction d'arbres phylogénétiques...).
Ce livre aborde de manière simple les taches courantes en bioinformatique qu'un biologiste/biochimiste doit savoir traiter par lui-même sans avoir recours au spécialiste. Conçu de manière à faciliter la compréhension des approches, méthodes, algorithmes et implémentations les plus courantes en bioinformatique moléculaire et structurale, ce livre leur permettra d'éviter les pièges classiques et de répondre aux questions usuelles : comment chercher dans les banques de données biologiques ? Peut-on reconstruire l'histoire évolutive des espèces grâce aux séquences biologiques ? Quelle peut être la fonction d'une protéine ? Comment construire un modèle 3D de protéine ? Chaque chapitre se termine par une série de QCM corrigés.
Dans cette seconde édition, le chapitre sur les bases de données a été entièrement mis à jour et un cas pratique détaillé supplémentaire a été ajouté.Bioinformatique : cours et applications [texte imprimé] / Gilbert Deléage (1956-...), Auteur ; Manolo Gouy (19..-....), Auteur . - 2 ed . - Paris (France) : Dunod, 2015 . - 1 vol. (XI-203 p.) : ill., graph., fig., tabl., couv. ill. en coul. ; 24 cm. - (Sciences sup, ISSN 1636-2241) .
ISBN : 978-2-10-072752-0
Langues : Français
Catégories : Bio-informatique - Biostatistiques - Biomathématique - Mathématique - Informatique Mots-clés : Bioinformatique Index. décimale : 570.285 Informatique appliquée à la biologie et aux sciences de la vie - bio-informatique - Résumé :
La bioinformatique est une "interdiscipline" à la frontière de la biologie, de l'informatique et des mathématiques. Elle a pour but d'intégrer des données d'origines très diverses pour modéliser les systèmes vivants afin de comprendre et prédire leurs comportements (analyse du génome, modélisation de l'évolution d'une population animale dans un environnement donné, modélisation moléculaire, reconstruction d'arbres phylogénétiques...).
Ce livre aborde de manière simple les taches courantes en bioinformatique qu'un biologiste/biochimiste doit savoir traiter par lui-même sans avoir recours au spécialiste. Conçu de manière à faciliter la compréhension des approches, méthodes, algorithmes et implémentations les plus courantes en bioinformatique moléculaire et structurale, ce livre leur permettra d'éviter les pièges classiques et de répondre aux questions usuelles : comment chercher dans les banques de données biologiques ? Peut-on reconstruire l'histoire évolutive des espèces grâce aux séquences biologiques ? Quelle peut être la fonction d'une protéine ? Comment construire un modèle 3D de protéine ? Chaque chapitre se termine par une série de QCM corrigés.
Dans cette seconde édition, le chapitre sur les bases de données a été entièrement mis à jour et un cas pratique détaillé supplémentaire a été ajouté.Exemplaires
Code-barres Cote Support Localisation Section Disponibilité FB/10866 SNV8/1270 Livre Bibliothèque SNV Français Disponible FB/10870 SNV8/1270 Livre Bibliothèque SNV Français Disponible FB/10869 SNV8/1270 Livre Bibliothèque SNV Français Disponible FB/10868 SNV8/1270 Livre Bibliothèque SNV Français Disponible FB/10867 SNV8/1270 Livre Bibliothèque SNV Français Disponible
Titre : Computational Genomics with R Type de document : texte imprimé Auteurs : Altuna Akalin, Auteur Editeur : London : CRC press Année de publication : 2023 Collection : Computational Biology Series Importance : 1 vol. (440 p.) Présentation : ill.en coul. Format : 26 cm ISBN/ISSN/EAN : 978-0-367-63460-5 Langues : Anglais Catégories : Bio-informatique - Biostatistiques - Biomathématique - Mathématique - Informatique Mots-clés : Informatique Index. décimale : 570.285 Informatique appliquée à la biologie et aux sciences de la vie - bio-informatique - Résumé :
Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology.
After reading:
* You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages.
* You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data.
* You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation.
* You will know the basics of processing and quality checking high-throughput sequencing data.
* You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites.
* You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization.
* You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq.
* You will know basic techniques for integrating and interpreting multi-omics datasets.
Note de contenu :
Sommaire:
-1- Introduction to Genomics
-2- Introduction to R for Genomic Data Analysis
-3- Statistics for Genomics
-4- Exploratory Data Analysis with Unsupervised Machine Learning
-5- Predictive Modeling with Supervised Machine Learning
-6- Operations on Genomic Intervals and Genome Arithmetic
-7- Quality Check, Processing and Alignment of High-throughput Sequencing Reads
-8- RNA-seq Analysis
-9- ChIP-seq analysis
-10 DNA methylation analysis using bisulfite sequencing data
-11 Multi-omics AnalysisComputational Genomics with R [texte imprimé] / Altuna Akalin, Auteur . - London : CRC press, 2023 . - 1 vol. (440 p.) : ill.en coul. ; 26 cm. - (Computational Biology Series) .
ISBN : 978-0-367-63460-5
Langues : Anglais
Catégories : Bio-informatique - Biostatistiques - Biomathématique - Mathématique - Informatique Mots-clés : Informatique Index. décimale : 570.285 Informatique appliquée à la biologie et aux sciences de la vie - bio-informatique - Résumé :
Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology.
After reading:
* You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages.
* You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data.
* You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation.
* You will know the basics of processing and quality checking high-throughput sequencing data.
* You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites.
* You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization.
* You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq.
* You will know basic techniques for integrating and interpreting multi-omics datasets.
Note de contenu :
Sommaire:
-1- Introduction to Genomics
-2- Introduction to R for Genomic Data Analysis
-3- Statistics for Genomics
-4- Exploratory Data Analysis with Unsupervised Machine Learning
-5- Predictive Modeling with Supervised Machine Learning
-6- Operations on Genomic Intervals and Genome Arithmetic
-7- Quality Check, Processing and Alignment of High-throughput Sequencing Reads
-8- RNA-seq Analysis
-9- ChIP-seq analysis
-10 DNA methylation analysis using bisulfite sequencing data
-11 Multi-omics AnalysisExemplaires
Code-barres Cote Support Localisation Section Disponibilité FB/15764 SNV8/1823 Livre Bibliothèque SNV Englais Disponible FB/15765 SNV8/1823 Livre Bibliothèque SNV Englais Disponible Documents numériques
https://www.amazon.com/Computational-Genomics-Chapman-Hall-Biology/dp/0367634600URL
Titre : Computational Intelligence Techniques for Green Smart Cities Type de document : texte imprimé Auteurs : Mohamed Lahby, Auteur ; Ala Al-Fuqaha, Auteur ; Yassine Maleh, Auteur Editeur : Springer Année de publication : 2022 Collection : Green energy and technology Importance : 1 vol. (419 p.) Présentation : ill.en coul. Format : 25 cm ISBN/ISSN/EAN : 978-3-030-96428-3 Langues : Français Catégories : Bio-informatique - Biostatistiques - Biomathématique - Mathématique - Informatique Index. décimale : 570.285 Informatique appliquée à la biologie et aux sciences de la vie - bio-informatique - Résumé :
This book contains high-quality and original research on computational intelligence for green smart cities research. In recent years, the use of smart city technology has rapidly increased through the successful development and deployment of Internet of Things (IoT) architectures. The citizens' quality of life has been improved in several sensitive areas of the city, such as transportation, buildings, health care, education, environment, and security, thanks to these technological advances.
Computational intelligence techniques and algorithms enable a computational analysis of enormous data sets to reveal patterns that recur. This information is used to inform and improve decision-making at the municipal level to build smart computational intelligence techniques and sustainable cities for their citizens. Machine intelligence allows us to identify trends (patterns). The smart city could better integrate its transportation network, for example. By offering a better public transportation network adapted to the demand, we could reduce personal vehicles and energy consumption. A smart city could use models to predict the consequences of a change, such as pedestrianizing a street or adding a bike lane. A city can even create a 3D digital twin to test hypothetical projects.
This book comprises many state-of-the-art contributions from scientists and practitioners working in machine intelligence and green smart cities. It aspires to provide a relevant reference for students, researchers, engineers, and professionals working in this area or those interested in grasping its diverse facets and exploring the latest advances in machine intelligence for green and sustainable smart city applications.Note de contenu :
Sommaire:
- Machine Learning Techniques for Renewable Energy Forecasting: A Comprehensive Review
- Machine Learning for Green Smart Homes
- Artificial Intelligence Based Smart Waste Management—A Systematic Review
- Machine Learning and Green Transportation
- Traffic Sign Detection for Green Smart Public Transportation Vehicles Based on Light Neural Network Model
- Green Transportation Balanced Scorecard Model: A Fuzzy-Delphi Approach During COVID-19
- Green Smart City Intelligent and Cyber-Security-Based IoT Transportation Solutions for Combating the Pandemic COVID-19Computational Intelligence Techniques for Green Smart Cities [texte imprimé] / Mohamed Lahby, Auteur ; Ala Al-Fuqaha, Auteur ; Yassine Maleh, Auteur . - [S.l.] : Springer, 2022 . - 1 vol. (419 p.) : ill.en coul. ; 25 cm. - (Green energy and technology) .
ISBN : 978-3-030-96428-3
Langues : Français
Catégories : Bio-informatique - Biostatistiques - Biomathématique - Mathématique - Informatique Index. décimale : 570.285 Informatique appliquée à la biologie et aux sciences de la vie - bio-informatique - Résumé :
This book contains high-quality and original research on computational intelligence for green smart cities research. In recent years, the use of smart city technology has rapidly increased through the successful development and deployment of Internet of Things (IoT) architectures. The citizens' quality of life has been improved in several sensitive areas of the city, such as transportation, buildings, health care, education, environment, and security, thanks to these technological advances.
Computational intelligence techniques and algorithms enable a computational analysis of enormous data sets to reveal patterns that recur. This information is used to inform and improve decision-making at the municipal level to build smart computational intelligence techniques and sustainable cities for their citizens. Machine intelligence allows us to identify trends (patterns). The smart city could better integrate its transportation network, for example. By offering a better public transportation network adapted to the demand, we could reduce personal vehicles and energy consumption. A smart city could use models to predict the consequences of a change, such as pedestrianizing a street or adding a bike lane. A city can even create a 3D digital twin to test hypothetical projects.
This book comprises many state-of-the-art contributions from scientists and practitioners working in machine intelligence and green smart cities. It aspires to provide a relevant reference for students, researchers, engineers, and professionals working in this area or those interested in grasping its diverse facets and exploring the latest advances in machine intelligence for green and sustainable smart city applications.Note de contenu :
Sommaire:
- Machine Learning Techniques for Renewable Energy Forecasting: A Comprehensive Review
- Machine Learning for Green Smart Homes
- Artificial Intelligence Based Smart Waste Management—A Systematic Review
- Machine Learning and Green Transportation
- Traffic Sign Detection for Green Smart Public Transportation Vehicles Based on Light Neural Network Model
- Green Transportation Balanced Scorecard Model: A Fuzzy-Delphi Approach During COVID-19
- Green Smart City Intelligent and Cyber-Security-Based IoT Transportation Solutions for Combating the Pandemic COVID-19Exemplaires
Code-barres Cote Support Localisation Section Disponibilité FB/15766 SNV8/1824 Livre Bibliothèque SNV Englais Disponible Documents numériques
https://www.amazon.com/Computational-Intelligence-Techniques-Cities-Technology-ebook/dp/B09YNHG3WR/ref=sr_1_1?crid=2DNPBJD0A1NRG&dib=eyJ2IjoiMSJ9.wCqvnYsA32fVXwHwlzBENA.r0m54vbQmLhU5nRH0Ho17lPalmkLnbgERaqlpJWL2sE&dib_tag=se&keywords=9783030964283&qid=1736URL
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PermalinkEssentials of bioinfortmatics / Akansha Singh / Burlington [Canada] : Delve Publishing (2024)
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