In addition to statistical methods, informatics techniques are also very powerful for extracting scientific information from observational data. These types of techniques have close links with information theory, signal processing and computational harmonic analysis. Wavelet methods, for example, allow one to probe both spatial- and scale-dependent signal characteristics simultaneously. Such techniques are very useful in studying physical phenomena since many physical processes are manifest on particular physical scales, while also spatially localised. Recent developments in this domain have led to the theory of compressive sensing, a revolutionary breakthrough in the field of sampling theory, which provides a powerful framework for solving inverse problems. Finally, it is important to recognise that deep connections can often be made between statistical and informatics methodologies.