Quantitative biology is an umbrella term encompassing the use of mathematical, statistical or computational techniques to study life and living organisms. The central theme and goal of quantitative biology is the creation of predictive models based on fundamental principles governing living systems. [1] [2]
The subfields of biology that employ quantitative approaches include:
In vitro studies are performed with microorganisms, cells, or biological molecules outside their normal biological context. Colloquially called "test-tube experiments", these studies in biology and its subdisciplines are traditionally done in labware such as test tubes, flasks, Petri dishes, and microtiter plates. Studies conducted using components of an organism that have been isolated from their usual biological surroundings permit a more detailed or more convenient analysis than can be done with whole organisms; however, results obtained from in vitro experiments may not fully or accurately predict the effects on a whole organism. In contrast to in vitro experiments, in vivo studies are those conducted in living organisms, including humans, known as clinical trials, and whole plants.
Computational biology refers to the use of data analysis, mathematical modeling and computational simulations to understand biological systems and relationships. An intersection of computer science, biology, and big data, the field also has foundations in applied mathematics, chemistry, and genetics. It differs from biological computing, a subfield of computer engineering which uses bioengineering to build computers.
Computational neuroscience is a branch of neuroscience which employs mathematical models, computer simulations, theoretical analysis and abstractions of the brain to understand the principles that govern the development, structure, physiology and cognitive abilities of the nervous system.
Systems biology is the computational and mathematical analysis and modeling of complex biological systems. It is a biology-based interdisciplinary field of study that focuses on complex interactions within biological systems, using a holistic approach to biological research.
Mathematical and theoretical biology, or biomathematics, is a branch of biology which employs theoretical analysis, mathematical models and abstractions of the living organisms to investigate the principles that govern the structure, development and behavior of the systems, as opposed to experimental biology which deals with the conduction of experiments to prove and validate the scientific theories. The field is sometimes called mathematical biology or biomathematics to stress the mathematical side, or theoretical biology to stress the biological side. Theoretical biology focuses more on the development of theoretical principles for biology while mathematical biology focuses on the use of mathematical tools to study biological systems, even though the two terms are sometimes interchanged.
'Biocomplexity' is a multidisciplinary field that examines and investigates emergent properties arising from the interaction of multiple biological agents, phenomena, and systems, which may range in spatiotemporal scales, biological relationships,interactions and levels from molecules to ecosystems. Research in this area investigates the nonlinear or chaotic dynamics, unpredictable behavior, self-organization, and adaptation of living systems, aware that biological systems can display characteristics that cannot be understood through the study of individual properties alone.
Modelling biological systems is a significant task of systems biology and mathematical biology. Computational systems biology aims to develop and use efficient algorithms, data structures, visualization and communication tools with the goal of computer modelling of biological systems. It involves the use of computer simulations of biological systems, including cellular subsystems, to both analyze and visualize the complex connections of these cellular processes.
In biology, the nuclear matrix is the network of fibres found throughout the inside of a cell nucleus after a specific method of chemical extraction. According to some it is somewhat analogous to the cell cytoskeleton. In contrast to the cytoskeleton, however, the nuclear matrix has been proposed to be a dynamic structure. Along with the nuclear lamina, it supposedly aids in organizing the genetic information within the cell.
The Systems Biology Ontology (SBO) is a set of controlled, relational vocabularies of terms commonly used in systems biology, and in particular in computational modeling.
Molecular biophysics is a rapidly evolving interdisciplinary area of research that combines concepts in physics, chemistry, engineering, mathematics and biology. It seeks to understand biomolecular systems and explain biological function in terms of molecular structure, structural organization, and dynamic behaviour at various levels of complexity. This discipline covers topics such as the measurement of molecular forces, molecular associations, allosteric interactions, Brownian motion, and cable theory. Additional areas of study can be found on Outline of Biophysics. The discipline has required development of specialized equipment and procedures capable of imaging and manipulating minute living structures, as well as novel experimental approaches.
The branches of science, also referred to as sciences, scientific fields or scientific disciplines, are commonly divided into three major groups:
Robert F. Murphy is Ray and Stephanie Lane Professor of Computational Biology Emeritus and Director of the M.S. Program in Automated Science at Carnegie Mellon University. Prior to his retirement in May 2021, he was the Ray and Stephanie Lane Professor of Computational Biology as well as Professor of Biological Sciences, Biomedical Engineering, and Machine Learning. He was founding Director of the Center for Bioimage Informatics at Carnegie Mellon and founded the Joint CMU-Pitt Ph.D. Program in Computational Biology. He also founded the Computational Biology Department at Carnegie Mellon University and served as its head from 2009 to 2020.
This is a bibliography of ecology.
An autapse is a chemical or electrical synapse from a neuron onto itself. It can also be described as a synapse formed by the axon of a neuron on its own dendrites, in vivo or in vitro.
Cancer systems biology encompasses the application of systems biology approaches to cancer research, in order to study the disease as a complex adaptive system with emerging properties at multiple biological scales. Cancer systems biology represents the application of systems biology approaches to the analysis of how the intracellular networks of normal cells are perturbed during carcinogenesis to develop effective predictive models that can assist scientists and clinicians in the validations of new therapies and drugs. Tumours are characterized by genomic and epigenetic instability that alters the functions of many different molecules and networks in a single cell as well as altering the interactions with the local environment. Cancer systems biology approaches, therefore, are based on the use of computational and mathematical methods to decipher the complexity in tumorigenesis as well as cancer heterogeneity.
John J. Tyson is an American systems biologist and mathematical biologist who serves as University Distinguished Professor of Biology at Virginia Tech, and is the former president of the Society for Mathematical Biology. He is known for his research on biochemical switches in the cell cycle, dynamics of biological networks and on excitable media.
Sherrie Lynne Lyons is an American author, science historian and skeptic.
Hanah Margalit is a Professor in the faculty of medicine at the Hebrew University of Jerusalem. Her research combines bioinformatics, computational biology and systems biology, specifically in the fields of gene regulation in bacteria and eukaryotes.
Genome Informatics is a scientific study of information processing in genomes.
Stacey Finley is the Nichole A. and Thuan Q. Pham Professor and associate professor of chemical engineering and materials science, and quantitative and computational biology at the University of Southern California. Finley has a joint appointment in the department of chemical engineering and materials science, and she is a member of the USC Norris Comprehensive Cancer Center. Finley is also a standing member of the MABS Study Section at NIH. Her research has been supported by grants from the NSF, NIH, and American Cancer Society.