Search
- Filter Results
- Location
- Classification
- Include attachments
- https://bio.libretexts.org/Bookshelves/Biochemistry/Fundamentals_of_Biochemistry_(Jakubowski_and_Flatt)/01%3A_Unit_I-_Structure_and_Catalysis/02%3A_Water_and_its_Role_in_Life/2.03%3A_Buffering_against_pH_Changes_in_Biological_SystemsThis page outlines several learning goals focused on understanding buffers in biochemical contexts. These goals include defining buffer characteristics, explaining buffer resistance to pH changes, and...This page outlines several learning goals focused on understanding buffers in biochemical contexts. These goals include defining buffer characteristics, explaining buffer resistance to pH changes, and the importance of buffers in biochemical homeostasis.
- https://bio.libretexts.org/Bookshelves/Biochemistry/Fundamentals_of_Biochemistry_(Jakubowski_and_Flatt)/01%3A_Unit_I-_Structure_and_Catalysis/11%3A_Biological_Membranes_and_Transport/11.01%3A_Membrane_and_Membrane_ProteinsThe page outlines advanced learning goals for junior and senior biochemistry majors, focusing on membrane proteins. Key topics include classifying membrane proteins, exploring differences between tran...The page outlines advanced learning goals for junior and senior biochemistry majors, focusing on membrane proteins. Key topics include classifying membrane proteins, exploring differences between transmembrane and peripheral proteins, understanding chemical anchors like lipid modifications, studying lipid aggregates for membrane protein research, and analyzing examples of transmembrane proteins such as channels, transporters, and receptors.
- https://bio.libretexts.org/Bookshelves/Introductory_and_General_Biology/Biology_(Kimball)/20%3A_General_ScienceThis page discusses the need for controlled experiments to establish causation between factors A and B, highlighting the impracticalities in human studies that lead to the use of epidemiological metho...This page discusses the need for controlled experiments to establish causation between factors A and B, highlighting the impracticalities in human studies that lead to the use of epidemiological methods. It emphasizes the importance of validating new drugs and treatments through clinical studies to ensure they improve upon existing methods. Additionally, it outlines the scientific approach, which combines common sense with specific characteristics that define scientific inquiry.
- https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Genetics_for_Plant_Breeding_(Suza_and_Lamkey)/01%3A_New_Page/1.14%3A_Plant_Breeding_BasicsThis page explores plant breeding fundamentals, data management, and statistical modeling techniques. Key topics include genetic improvement goals, mixed linear models, data types, and the significanc...This page explores plant breeding fundamentals, data management, and statistical modeling techniques. Key topics include genetic improvement goals, mixed linear models, data types, and the significance of exploratory data analysis (EDA). It discusses fixed vs. random effects, hypothesis testing, power of tests, and methods like ANOVA and AOC for data analysis. The use of R and RStudio for data manipulation is emphasized, alongside error types in statistical inference.
- https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Genetics_for_Plant_Breeding_(Suza_and_Lamkey)/01%3A_New_Page/1.07%3A_Estimates_of_VarianceThis page explores heritability estimation in quantitative genetics, focusing on genetic variance and covariance among relatives, particularly in plant breeding. It covers modeling genetic variance, d...This page explores heritability estimation in quantitative genetics, focusing on genetic variance and covariance among relatives, particularly in plant breeding. It covers modeling genetic variance, deriving variance components through ANOVA, and estimating variances in F2 and F3 progenies.
- https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Methods_for_Plant_Breeding_(Suza_and_Lamkey)/01%3A_Chapters/1.02%3A_Distributions_and_ProbabilityThis page covers the scientific method and experimental design principles, emphasizing the importance of proper sampling and data representation. It explains data visualization with histograms, introd...This page covers the scientific method and experimental design principles, emphasizing the importance of proper sampling and data representation. It explains data visualization with histograms, introduces statistical concepts such as quartiles, and discusses probability measures and distributions. The normal distribution is highlighted for its properties and use in probability calculations, including Z-scores.
- https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Methods_for_Plant_Breeding_(Suza_and_Lamkey)/01%3A_Chapters/1.09%3A_Two_Factor_ANOVAsThis page covers various aspects of experimental design and analysis in agricultural research, particularly focused on two-factor ANOVA. It compares factorial designs that consider interactions betwee...This page covers various aspects of experimental design and analysis in agricultural research, particularly focused on two-factor ANOVA. It compares factorial designs that consider interactions between treatment factors (like plant populations and nitrogen levels) with simpler experimental setups.
- https://bio.libretexts.org/Bookshelves/Biochemistry/Fundamentals_of_Biochemistry_(Jakubowski_and_Flatt)/01%3A_Unit_I-_Structure_and_Catalysis/02%3A_Water_and_its_Role_in_Life/2.02%3A_Weak_Acids_and_Bases_pH_and_pKaThis page discusses fundamental concepts of biochemistry, focusing on acids, bases, and pKa. It outlines the properties and significance of strong and weak acids and bases in biochemical contexts and ...This page discusses fundamental concepts of biochemistry, focusing on acids, bases, and pKa. It outlines the properties and significance of strong and weak acids and bases in biochemical contexts and introduces the concept of pKa to describe acid strength. The page also explains the application of the Henderson-Hasselbalch equation for calculating pH and discusses titration curves, buffering regions, and the prediction of protonation states in biochemical systems.
- https://bio.libretexts.org/Bookshelves/Biochemistry/Fundamentals_of_Biochemistry_(Jakubowski_and_Flatt)/01%3A_Unit_I-_Structure_and_Catalysis/02%3A_Water_and_its_Role_in_Life/2.04%3A_Solubility_in_an_aqueous_world_-_noncovalent_interactions_in_depthThe page provides an in-depth exploration of noncovalent interactions within biochemistry, touching on hydrogen bonding, ionic interactions, van der Waals forces, and more. It connects these interacti...The page provides an in-depth exploration of noncovalent interactions within biochemistry, touching on hydrogen bonding, ionic interactions, van der Waals forces, and more. It connects these interactions to water???s properties, explaining how they influence solubility and biological structures such as protein folding.
- https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Methods_for_Plant_Breeding_(Suza_and_Lamkey)/01%3A_Chapters/1.11%3A_Randomized_Complete_Block_DesignThis page emphasizes the significance of using Randomized Complete Block Design (RCBD) in field experiments to minimize confounding factors and improve analysis accuracy through blocking. It outlines ...This page emphasizes the significance of using Randomized Complete Block Design (RCBD) in field experiments to minimize confounding factors and improve analysis accuracy through blocking. It outlines methods for randomization, contrasts RCBD with Completely Randomized Design (CRD), and discusses the importance of Analysis of Variance (ANOVA) in evaluating treatment effects.
- https://bio.libretexts.org/Bookshelves/Agriculture_and_Horticulture/Quantitative_Methods_for_Plant_Breeding_(Suza_and_Lamkey)/01%3A_Chapters/1.12%3A_Data_TransformationThis page covers the key assumptions of ANOVA, emphasizing the importance of normality of error terms, homogeneity of variances, and additivity of effects. It discusses methods for testing variances l...This page covers the key assumptions of ANOVA, emphasizing the importance of normality of error terms, homogeneity of variances, and additivity of effects. It discusses methods for testing variances like Bartlett's Test, highlights data transformation options, and provides practical examples related to gamagrass seed treatments.
