Items related to The Learning Framework in Chemoinformatics: A Mathematical...
The Learning Framework in Chemoinformatics: A Mathematical and Python-Based Exploration of Aspirin (Acetylsalicylic Acid) - Softcover
Synopsis
The Learning Framework in Chemoinformatics: A Mathematical and Python-Based Exploration of Aspirin (Acetylsalicylic Acid) presents an accessible introduction to the interdisciplinary world of chemistry, mathematics, and computational science. Using aspirin as a model compound, Dr. Sunil Maria Benedict guides readers through the fundamental concepts of molecular mass determination, elemental percentage composition, stoichiometry, and computational verification using Python. Rather than treating chemical calculations as isolated arithmetic exercises, this work introduces a structured learning framework that encourages learners to understand each stage of the calculation process. By combining manual mathematical reasoning with computational analysis, the book demonstrates how foundational chemistry can be reinforced through programming, data visualisation, and reproducible scientific workflows. Beginning with the chemical structure and properties of acetylsalicylic acid, the discussion expands into the principles of chemoinformatics, molecular representation, and computational thinking. Readers are introduced to Python-based analyses, graphical visualisations, statistical verification, and reproducible computational methods that mirror modern scientific practice while remaining accessible to beginners. Designed for students of chemistry, pharmacy, bioinformatics, biotechnology, life sciences, and computational sciences, this volume serves as both a practical learning resource and an introduction to contemporary computational chemistry. The manuscript also highlights the educational value of integrating mathematics, chemistry, and programming into a single coherent framework that promotes conceptual understanding rather than rote memorisation. Combining scientific accuracy with an instructional approach, this work demonstrates how a familiar pharmaceutical compound can become a gateway to the broader fields of chemoinformatics and computational science. It offers educators, researchers, and students a clear pathway from foundational chemical principles to reproducible computational analysis, fostering analytical thinking, interdisciplinary learning, and confiden
"synopsis" may belong to another edition of this title.
Search results for The Learning Framework in Chemoinformatics: A Mathematical...
Stock Image
The Learning Framework in Chemoinformatics (Paperback)
Print on DemandSeller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Seller rating 5 out of 5 stars
Paperback. Condition: new. Paperback. The Learning Framework in Chemoinformatics: A Mathematical and Python-Based Exploration of Aspirin (Acetylsalicylic Acid) presents an accessible introduction to the interdisciplinary world of chemistry, mathematics, and computational science. Using aspirin as a model compound, Dr. Sunil Maria Benedict guides readers through the fundamental concepts of molecular mass determination, elemental percentage composition, stoichiometry, and computational verification using Python. Rather than treating chemical calculations as isolated arithmetic exercises, this work introduces a structured learning framework that encourages learners to understand each stage of the calculation process. By combining manual mathematical reasoning with computational analysis, the book demonstrates how foundational chemistry can be reinforced through programming, data visualisation, and reproducible scientific workflows. Beginning with the chemical structure and properties of acetylsalicylic acid, the discussion expands into the principles of chemoinformatics, molecular representation, and computational thinking. Readers are introduced to Python-based analyses, graphical visualisations, statistical verification, and reproducible computational methods that mirror modern scientific practice while remaining accessible to beginners. Designed for students of chemistry, pharmacy, bioinformatics, biotechnology, life sciences, and computational sciences, this volume serves as both a practical learning resource and an introduction to contemporary computational chemistry. The manuscript also highlights the educational value of integrating mathematics, chemistry, and programming into a single coherent framework that promotes conceptual understanding rather than rote memorisation. Combining scientific accuracy with an instructional approach, this work demonstrates how a familiar pharmaceutical compound can become a gateway to the broader fields of chemoinformatics and computational science. It offers educators, researchers, and students a clear pathway from foundational chemical principles to reproducible computational analysis, fostering analytical thinking, interdisciplinary learning, and confiden This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9789999350617
Stock Image
The Learning Framework in Chemoinformatics: A Mathematical and Python-Based Exploration of Aspirin (Acetylsalicylic Acid)
Seller: California Books, Miami, FL, U.S.A.
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # I-9789999350617
Stock Image
The Learning Framework in Chemoinformatics
Print on DemandSeller: PBShop.store US, Wood Dale, IL, U.S.A.
Seller rating 5 out of 5 stars
PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Seller Inventory # L0-9789999350617
Stock Image
The Learning Framework in Chemoinformatics
Print on DemandSeller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 5 out of 5 stars
PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Seller Inventory # L0-9789999350617
Buy New
US$ 52.60
US$ 4.43 shipping
Ships from United Kingdom to U.S.A.
Ships from United Kingdom to U.S.A.
Quantity: Over 20 available
Stock Image
The Learning Framework in Chemoinformatics: A Mathematical and Python-Based Exploration of Aspirin (Acetylsalicylic Acid)
Seller: Revaluation Books, Exeter, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: Brand New. 41 pages. 6.00x0.10x9.00 inches. In Stock. Seller Inventory # x-9999350615
Buy New
US$ 48.10
US$ 13.46 shipping
Ships from United Kingdom to U.S.A.
Ships from United Kingdom to U.S.A.
Quantity: 2 available
Stock Image
The Learning Framework in Chemoinformatics
Print on DemandSeller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 42 pp. Englisch. Seller Inventory # 9789999350617
Buy New
US$ 49.38
US$ 25.82 shipping
Ships from Germany to U.S.A.
Ships from Germany to U.S.A.
Quantity: 2 available
Stock Image
The Learning Framework in Chemoinformatics (Paperback)
Print on DemandSeller: AussieBookSeller, Truganina, VIC, Australia
Seller rating 5 out of 5 stars
Paperback. Condition: new. Paperback. The Learning Framework in Chemoinformatics: A Mathematical and Python-Based Exploration of Aspirin (Acetylsalicylic Acid) presents an accessible introduction to the interdisciplinary world of chemistry, mathematics, and computational science. Using aspirin as a model compound, Dr. Sunil Maria Benedict guides readers through the fundamental concepts of molecular mass determination, elemental percentage composition, stoichiometry, and computational verification using Python. Rather than treating chemical calculations as isolated arithmetic exercises, this work introduces a structured learning framework that encourages learners to understand each stage of the calculation process. By combining manual mathematical reasoning with computational analysis, the book demonstrates how foundational chemistry can be reinforced through programming, data visualisation, and reproducible scientific workflows. Beginning with the chemical structure and properties of acetylsalicylic acid, the discussion expands into the principles of chemoinformatics, molecular representation, and computational thinking. Readers are introduced to Python-based analyses, graphical visualisations, statistical verification, and reproducible computational methods that mirror modern scientific practice while remaining accessible to beginners. Designed for students of chemistry, pharmacy, bioinformatics, biotechnology, life sciences, and computational sciences, this volume serves as both a practical learning resource and an introduction to contemporary computational chemistry. The manuscript also highlights the educational value of integrating mathematics, chemistry, and programming into a single coherent framework that promotes conceptual understanding rather than rote memorisation. Combining scientific accuracy with an instructional approach, this work demonstrates how a familiar pharmaceutical compound can become a gateway to the broader fields of chemoinformatics and computational science. It offers educators, researchers, and students a clear pathway from foundational chemical principles to reproducible computational analysis, fostering analytical thinking, interdisciplinary learning, and confiden This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9789999350617
Buy New
US$ 53.59
US$ 37.00 shipping
Ships from Australia to U.S.A.
Ships from Australia to U.S.A.
Quantity: 1 available
Stock Image
The Learning Framework in Chemoinformatics (Paperback)
Print on DemandSeller: CitiRetail, Stevenage, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: new. Paperback. The Learning Framework in Chemoinformatics: A Mathematical and Python-Based Exploration of Aspirin (Acetylsalicylic Acid) presents an accessible introduction to the interdisciplinary world of chemistry, mathematics, and computational science. Using aspirin as a model compound, Dr. Sunil Maria Benedict guides readers through the fundamental concepts of molecular mass determination, elemental percentage composition, stoichiometry, and computational verification using Python. Rather than treating chemical calculations as isolated arithmetic exercises, this work introduces a structured learning framework that encourages learners to understand each stage of the calculation process. By combining manual mathematical reasoning with computational analysis, the book demonstrates how foundational chemistry can be reinforced through programming, data visualisation, and reproducible scientific workflows. Beginning with the chemical structure and properties of acetylsalicylic acid, the discussion expands into the principles of chemoinformatics, molecular representation, and computational thinking. Readers are introduced to Python-based analyses, graphical visualisations, statistical verification, and reproducible computational methods that mirror modern scientific practice while remaining accessible to beginners. Designed for students of chemistry, pharmacy, bioinformatics, biotechnology, life sciences, and computational sciences, this volume serves as both a practical learning resource and an introduction to contemporary computational chemistry. The manuscript also highlights the educational value of integrating mathematics, chemistry, and programming into a single coherent framework that promotes conceptual understanding rather than rote memorisation. Combining scientific accuracy with an instructional approach, this work demonstrates how a familiar pharmaceutical compound can become a gateway to the broader fields of chemoinformatics and computational science. It offers educators, researchers, and students a clear pathway from foundational chemical principles to reproducible computational analysis, fostering analytical thinking, interdisciplinary learning, and confiden This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9789999350617
Buy New
US$ 48.49
US$ 49.79 shipping
Ships from United Kingdom to U.S.A.
Ships from United Kingdom to U.S.A.
Quantity: 1 available
Stock Image
The Learning Framework in Chemoinformatics : A Mathematical and Python-Based Exploration of Aspirin (Acetylsalicylic Acid)
Print on DemandSeller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The Learning Framework in Chemoinformatics: A Mathematical and Python-Based Exploration of Aspirin (Acetylsalicylic Acid) presents an accessible introduction to the interdisciplinary world of chemistry, mathematics, and computational science. Using aspirin as a model compound, Dr. Sunil Maria Benedict guides readers through the fundamental concepts of molecular mass determination, elemental percentage composition, stoichiometry, and computational verification using Python. Rather than treating chemical calculations as isolated arithmetic exercises, this work introduces a structured learning framework that encourages learners to understand each stage of the calculation process. By combining manual mathematical reasoning with computational analysis, the book demonstrates how foundational chemistry can be reinforced through programming, data visualisation, and reproducible scientific workflows. Beginning with the chemical structure and properties of acetylsalicylic acid, the discussion expands into the principles of chemoinformatics, molecular representation, and computational thinking. Readers are introduced to Python-based analyses, graphical visualisations, statistical verification, and reproducible computational methods that mirror modern scientific practice while remaining accessible to beginners. Designed for students of chemistry, pharmacy, bioinformatics, biotechnology, life sciences, and computational sciences, this volume serves as both a practical learning resource and an introduction to contemporary computational chemistry. The manuscript also highlights the educational value of integrating mathematics, chemistry, and programming into a single coherent framework that promotes conceptual understanding rather than rote memorisation. Combining scientific accuracy with an instructional approach, this work demonstrates how a familiar pharmaceutical compound can become a gateway to the broader fields of chemoinformatics and computational science. It offers educators, researchers, and students a clear pathway from foundational chemical principles to reproducible computational analysis, fostering analytical thinking, interdisciplinary learning, and confiden. Seller Inventory # 9789999350617
Buy New
US$ 63.03
US$ 39.30 shipping
Ships from Germany to U.S.A.
Ships from Germany to U.S.A.
Quantity: 2 available
Stock Image
The Learning Framework in Chemoinformatics
Print on DemandSeller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The Learning Framework in Chemoinformatics: A Mathematical and Python-Based Exploration of Aspirin (Acetylsalicylic Acid) presents an accessible introduction to the interdisciplinary world of chemistry, mathematics, and computational science. Using aspirin as a model compound, Dr. Sunil Maria Benedict guides readers through the fundamental concepts of molecular mass determination, elemental percentage composition, stoichiometry, and computational verification using Python. Rather than treating chemical calculations as isolated arithmetic exercises, this work introduces a structured learning framework that encourages learners to understand each stage of the calculation process. By combining manual mathematical reasoning with computational analysis, the book demonstrates how foundational chemistry can be reinforced through programming, data visualisation, and reproducible scientific workflows. Beginning with the chemical structure and properties of acetylsalicylic acid, the discussion expands into the principles of chemoinformatics, molecular representation, and computational thinking. Readers are introduced to Python-based analyses, graphical visualisations, statistical verification, and reproducible computational methods that mirror modern scientific practice while remaining accessible to beginners. Designed for students of chemistry, pharmacy, bioinformatics, biotechnology, life sciences, and computational sciences, this volume serves as both a practical learning resource and an introduction to contemporary computational chemistry. The manuscript also highlights the educational value of integrating mathematics, chemistry, and programming into a single coherent framework that promotes conceptual understanding rather than rote memorisation. Combining scientific accuracy with an instructional approach, this work demonstrates how a familiar pharmaceutical compound can become a gateway to the broader fields of chemoinformatics and computational science. It offers educators, researchers, and students a clear pathway from foundational chemical principles to reproducible computational analysis, fostering analytical thinking, interdisciplinary learning, and confiden 42 pp. Englisch. Seller Inventory # 9789999350617
Buy New
US$ 49.38
US$ 67.37 shipping
Ships from Germany to U.S.A.
Ships from Germany to U.S.A.
Quantity: 1 available