Bioinformatics
Bioinformatics and Computational biology are interdisciplinary fields of research, development and application of algorithms, computational and statistical methods for management and analysis of biological data, and for solving basic biological problems.
[−] Bioinformatics
[+] Bioinformaticists
[+] Bioinformatics algorithms
[+] Bioinformatics companies
[+] Bioinformatics software
[+] Biological sequence format
[+] Bioinformatics databases
[+] Microarrays
[+] Omics
[+] Bioinformatics organizations
[+] Phylogenetics
[+] Systems biology
[+] Theoretical biologists
[+] Theoretical biology
[+] Bioinformatics stubs
Saturday, December 5, 2009
Biostatistics journals
Biostatistics journals
Biometrics
Biometrika
Biostatistics
Pharmaceutical Statistics
Statistical Applications in Genetics and Molecular Biology
Related fields
Biostatistics shares several methods with quantitative fields such as:
statistics,
operations research,
computer science,
psychometrics,
econometrics, and
mathematical demography
See also
Quantitative parasitology
Ecological forecasting
Group size measures
Journals
Statistical Applications in Genetics and Molecular Biology
Statistics in Medicine
The International Journal of Biostatistics
Journal of Agricultural, Biological, and Environmental Statistics
Journal of Biopharmaceutical Statistics
Biostatistics
Biometrics
Biometrika
Biometrical Journl
Genetics Selection Evolution
Biometrics
Biometrika
Biostatistics
Pharmaceutical Statistics
Statistical Applications in Genetics and Molecular Biology
Related fields
Biostatistics shares several methods with quantitative fields such as:
statistics,
operations research,
computer science,
psychometrics,
econometrics, and
mathematical demography
See also
Quantitative parasitology
Ecological forecasting
Group size measures
Journals
Statistical Applications in Genetics and Molecular Biology
Statistics in Medicine
The International Journal of Biostatistics
Journal of Agricultural, Biological, and Environmental Statistics
Journal of Biopharmaceutical Statistics
Biostatistics
Biometrics
Biometrika
Biometrical Journl
Genetics Selection Evolution
Applications of Biostatistics
Applications of biostatistics
Public health, including epidemiology, health services research, nutrition, and environmental health
Design and analysis of clinical trials in medicine
Genomics, population genetics, in order to link variation in genotype with a variation in phenotype. This has been used in agriculture to improve crops and farm animals (animal breeding). In biomedical research, this work can assist in finding candidates for gene that can cause or influence predisposition to disease in human genetics
Ecology, ecological forecasting
Biological sequence analysis
Statistical methods are beginning to be integrated into medical informatics, public health informatics, and bioinformatics
Public health, including epidemiology, health services research, nutrition, and environmental health
Design and analysis of clinical trials in medicine
Genomics, population genetics, in order to link variation in genotype with a variation in phenotype. This has been used in agriculture to improve crops and farm animals (animal breeding). In biomedical research, this work can assist in finding candidates for gene that can cause or influence predisposition to disease in human genetics
Ecology, ecological forecasting
Biological sequence analysis
Statistical methods are beginning to be integrated into medical informatics, public health informatics, and bioinformatics
Biostatistics/history of biological thought
Biostatistics
Biostatistics (a combination of the words biology and statistics; sometimes referred to as biometry or biometrics) is the application of statistics to a wide range of topics in biology. The science of biostatistics encompasses the design of biological experiments, especially in medicine and agriculture; the collection, summarization, and analysis of data from those experiments; and the interpretation of, and inference from, the results.
Biostatistics and the history of biological thought
Biostatistical reasoning and modeling were of critical importance to the foundation theories of modern biology. In the early 1900s, after the rediscovery of Mendel's work, the conceptual gaps in understanding between genetics and evolutionary Darwinism led to vigorous debate between biometricians such as Walter Weldon and Karl Pearson and Mendelians such as Charles Davenport, William Bateson and Wilhelm Johannsen. By the 1930s statisticians and models built on statistical reasoning had helped to resolve these differences and to produce the neo-Darwinian modern evolutionary synthesis.
These individuals and the work of other biostatisticians, mathematical biologists, and statistically inclined geneticists helped bring together evolutionary biology and genetics into a consistent, coherent whole that could begin to be quantitatively modeled.
In parallel to this overall development, the pioneering work of D'Arcy Thompson in On Growth and Form also helped to add quantitative discipline to biological study.
Despite the fundamental importance and frequent necessity of statistical reasoning, there may nonetheless have been a tendency among biologists to distrust or deprecate results which are not qualitatively apparent. One anecdote describes Thomas Hunt Morgan banning the Frieden calculator from his department at Caltech, saying "Well, I am like a guy who is prospecting for gold along the banks of the Sacramento River in 1849. With a little intelligence, I can reach down and pick up big nuggets of gold. And as long as I can do that, I'm not going to let any people in my department waste scarce resources in placer mining. Educators are now adjusting their curricula to focus on more quantitative concepts and tools.
Biostatistics (a combination of the words biology and statistics; sometimes referred to as biometry or biometrics) is the application of statistics to a wide range of topics in biology. The science of biostatistics encompasses the design of biological experiments, especially in medicine and agriculture; the collection, summarization, and analysis of data from those experiments; and the interpretation of, and inference from, the results.
Biostatistics and the history of biological thought
Biostatistical reasoning and modeling were of critical importance to the foundation theories of modern biology. In the early 1900s, after the rediscovery of Mendel's work, the conceptual gaps in understanding between genetics and evolutionary Darwinism led to vigorous debate between biometricians such as Walter Weldon and Karl Pearson and Mendelians such as Charles Davenport, William Bateson and Wilhelm Johannsen. By the 1930s statisticians and models built on statistical reasoning had helped to resolve these differences and to produce the neo-Darwinian modern evolutionary synthesis.
These individuals and the work of other biostatisticians, mathematical biologists, and statistically inclined geneticists helped bring together evolutionary biology and genetics into a consistent, coherent whole that could begin to be quantitatively modeled.
In parallel to this overall development, the pioneering work of D'Arcy Thompson in On Growth and Form also helped to add quantitative discipline to biological study.
Despite the fundamental importance and frequent necessity of statistical reasoning, there may nonetheless have been a tendency among biologists to distrust or deprecate results which are not qualitatively apparent. One anecdote describes Thomas Hunt Morgan banning the Frieden calculator from his department at Caltech, saying "Well, I am like a guy who is prospecting for gold along the banks of the Sacramento River in 1849. With a little intelligence, I can reach down and pick up big nuggets of gold. And as long as I can do that, I'm not going to let any people in my department waste scarce resources in placer mining. Educators are now adjusting their curricula to focus on more quantitative concepts and tools.
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