Technology to Collect Data
Collecting biological data is far more efficient with technology, which enables researchers to gather vast amounts of information from various sources.
Sensors: Tiny sensors, like those in wearables or environmental monitors, collect real-time physiological and ecological data. For example, a continuous glucose monitor uses a sensor to track blood sugar levels, while a remote sensor in a forest can record temperature, humidity, and animal movement. IB Biology students should use sensors to measure abiotic variables such as temperature, light, intensity and pH. See B4.1.4
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Data from Databases: Researchers access and extract data from extensive public databases, such as the National Center for Biotechnology Information (NCBI) , to retrieve genetic sequences, protein structures, and other molecular information. This saves time and allows for large-scale comparative studies. IB Biology students should use databases to:
- extract information about genome size for different taxonomic groups. See A3.1.10
- explore genes and their polypeptide products. See D3.2.18
- search allele frequencies. See D4.1.10
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Data from Models and Simulations: Scientists construct models as artificial representations of natural phenomena. They
are useful when direct observation or experimentation is difficult. Models are simplifications of complex systems and can be physical representations, abstract diagrams, mathematical equations or algorithms. All models have limitations that
need to be considered in their application. Computational models simulate biological processes, such as protein folding or population dynamics. These simulations generate new data that can be used to predict outcomes and test hypotheses without the need for physical experiments. IB Biology students should:
are useful when direct observation or experimentation is difficult. Models are simplifications of complex systems and can be physical representations, abstract diagrams, mathematical equations or algorithms. All models have limitations that
need to be considered in their application. Computational models simulate biological processes, such as protein folding or population dynamics. These simulations generate new data that can be used to predict outcomes and test hypotheses without the need for physical experiments. IB Biology students should:
- model surface-area-to-volume relationship using cubes of different side lengths. See B2.3.6
- model the results of enzyme experiments by sketching graphs. See C1.1.8
- compare the growth of a population against the model of exponential growth. See C4.1.7 and C4.1.8
- understand the use of knockout organisms models in research. See D1.3.8
- modelling sexual and natural selection based on experimental control of selection pressures. See D4.1.8
- use a mesocosm model to investigate the effect of variables on ecosystem stability. See D4.2.4
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