1 / 25

Data in Biology

Data in Biology. Lousy data. Biological data, perhaps more than most other scientific data, has the following characteristics:. It is complex It is incomplete It is error prone It contains the answers to questions of biological function and indeed, dysfunction

angelito-barbosa
Télécharger la présentation

Data in Biology

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Data in Biology

  2. Lousy data • Biological data, perhaps more than most other scientific data, has the following characteristics: • It is complex • It is incomplete • It is error prone • It contains the answers to questions of biological function and indeed, dysfunction • It is in high demand by a community with difficult questions

  3. What is data? • Any quantifiable information (e.g., wing length, number of bristles, gene expression, frequency of albinos, etc.). • A single datum is not amenable to statistical analysis • Hence data needs to be obtained from a number of individuals or groups, not merely from a single individual, or at multiple times from the same individual.

  4. Examples of biological data • Ecological data • Behavioral data • Molecular data (DNA, protein) • Physiological data • Population genetic data • Quantitative genetic data • Etc.

  5. Why collect data? • To describe a behavior, a phenomenon, a structure, etc. • To test a hypothesis

  6. Data and hypotheses • Data are very important to the advancement of knowledge, but they are only half of the science. • Biological hypotheses (or research questions) and ideas are the other half.

  7. Data and hypotheses…contd. • Think of it in this way: • Hypotheses (= research questions) without data are not very useful, and • Data collected without hypotheses (or research questions; or haphazardly and without purpose) are wasted.

  8. Let’s explore the nature of data • When you collect biological data, what is the perhaps the most obvious and odd thing about it?

  9. Variation Sometimes it is obvious

  10. Variation Sometimes it is not

  11. Why is there variation?

  12. Variables under direct human control • If a bank offers an interest of 5%, then the relationship between the interest accumulated and the period of investment is linear • (y = 5x) • E.g., for $1000.00 invested: Year Int. accum. (% of cap.) 1 5 2 10 3 15 4 20 5 25 An important feature of such data is that there is only one value of the dependant variable for a given value of the explanatory variable.

  13. Variables not under direct human control • Growth rate (of fish, etc.) • Response of living organisms to treatment (drugs, hormones, feed, etc.) • Expression levels of a gene in different tissues • The DNA sequence of a given gene in different individuals • Daily rainfall in a given city • The number of mycorrhizal spores at different depths of a plant root • Etc.

  14. The changing face of biology Fig 1.1 from Biometry by Sokal and Rohlf (3rd editiion), 1995

  15. Why?? • Biology has gone beyond the descriptive phase. • Need answers to “how” and “why” and not merely “what”. • Processes involved in answering these questions are not deterministic in their effects. • Stochastic or “random” effects present that cannot be individually identified.

  16. Boring vs Interesting Data • If the response can be determined exactly (no variation), this is deterministic – not in the realm of statistics • If response varies randomly, then such data is amenable to statistical analysis

  17. The free-kick, friends and growth

  18. What to do with data? • OK, let us assume you have collected the required data (which is a whole chapter in itself). • The data refers to the standard length of 1000 tilapia (Oreochromis niloticus) fry • What do you do with it?

  19. Frequency Distributions Figure 2.1 from Biometry by Sokal and Rohlf, 3rd edition, 1995

  20. Distribution of a variable • Shape of frequency distribution • Most shapes can be approximated mathematicallly • Of considerable biological interest

  21. Histogram

  22. Bar diagrams This bar diagram shows the photosynthesis of three aquatic plants during experiments when they were exposed to UV light. The first group of bars shows that all three plants were healthy at the start of the experiment. The second group shows that after 5 hours of UV light one plant is still healthy but the other two are under stress. The third group shows photosynthesis after the plants were left for 20 hours with the UV lights turned off – one plant did not completely recover.

  23. Leaf Leaf Stem Stem 3 5 8 7 2 8 4 5 6 7 0 2 6 7 1 6 9 3 5 2 7 8 4 5 6 7 8 0 2 6 7 1 6 9 6 7 8 9 10 6 7 8 9 10 after sorting Stem and Leaf Plots • Total length of 17 aphids (mm x 10) 8.8, 8.4, 9.0, 9.2, 10.1, 6.3, 7.8, 10.6, 10.9, 6.5, 7.7, 7.2, 8.6, 9.6, 8.5, 9.7, 8.7

More Related