ConvergenceInformatics
Chapter 3 & 4 (Week 2)Applications of Informatics
DCCS326 Korea University 2019 Fall
Asst. Prof. Minseok [email protected]
Contents
Statistics in Informatics
Introduction to Statistics2.
Pharmacoinformatics
Applications of Informatics (Cont.)1. Bioinformatics
Types of variables
Population and Sample
Fundamental notation
Central location and variability
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PharmacoinformaticsApplications of informatics in pharmacology
Drug discovery and development requires the integration ofmultiple scientific and technological disciplines.
These include chemistry, biology, pharmacology, pharmaceutical technology and extensive use of information technology.
From Wikipedia with “Pharmacoinformatics”
Pharmacoinformatics is also one of representative multidisciplinary fields
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PharmacoinformaticsApplications of informatics in pharmacology
The main idea behind the field is to integrate different informaticsbranches such as bioinformatics, chemoinformatics,immunoinformatics, and etc., into a single platform, resulting in aseamless process of drug discovery.
The first reference of the term "Pharmacoinformatics" can befound in the year of 1993.
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Medication use processPharmacoinformatics
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Medication with InformaticsPharmacoinformatics
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Concept of convergencePharmacoinformatics
EHR is a key for pharmacoinformatics
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BioinformaticsApplications of informatics in Biology
Bioinformatics is an interdisciplinary field that develops methodsand software tools for understanding biological data.
As an interdisciplinary field of science, bioinformatics combines biology, computer science, information engineering, mathematics and statistics to analyze and interpret biological data.
From Wikipedia with “Bioinformatics”
Bioinformatics is also one of representative multidisciplinary fields !
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BioinformaticsApplications of informatics in biology
Bioinformatics has been used for in silico analyses of biological queriesusing mathematical and statistical techniques.
Bioinformatics is both an umbrella term for the body of biologicalstudies that use computer programming as part of their methodology,as well as a reference to specific analysis "pipelines" that arerepeatedly used, particularly in the field of genomics.
In the biologist perspective,
the algorithms and techniques of computer science and statistics arebeing used to resolve the problem faced by molecular biology.
From the point of view of a computer scientist or statistician,
Information technology applied to the management and analysis ofbiological data.
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Subfields of BioinformaticsApplications of informatics in biology
Molecular Medicine Gene Therapy Drug Development ??? Pharmacoinformatics Microbial genome applications Crop improvement Animal breeding Forensic analysis Biotechnology Evolution analysis Bio weapon generation Human disease…
Bioinformatics is already essential for any molecular researches on all livingthings we can think of.
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Central Dogma in BiologyApplications of informatics in biology
Biological data can be roughly divided into three types, DNA, RNA, and Protein.
Each of the three types of data has different characteristics.
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Central Dogma in BiologyApplications of informatics in biology
Currently, Bioinformatics is currently the most representative of all Informaticsapplications.
That says, if you know how to do Bioinformatics, expanding to other fieldswill be very easy.
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StatisticsBasic concepts in Statistics for Informatics
Descriptive statistics
Inferential statistics
Statistics:To collect, organize, and summarize dataObserve only a portion, draw information on the whole
Biostatistics:
Statistics are used in diverse fieldCharacteristics of biological dataMolecular biology, public health, and biomedical data
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Variables and Random variableBasic concepts in Statistics for Informatics
Variables
• One of major purposes of statistics in public health is to find out thefactors and explain how
• If everyone has one value (constants, not variable), it is impossible tosee different health outcomes by this factor
Random variable
• Values of the variable are observed with certain probability rules.
• In probability and statistics, a random variable, random quantity,aleatory variable, or stochastic variable is described informally as avariable whose values depend on outcomes of a random phenomenon.
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Quantitative and qualitative variablesBasic concepts in Statistics for Informatics
Quantitative variables
Qualitative variables
• Continuous and numerical characteristics
• Categorical and non-numerical characteristics
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Population and SampleBasic concepts in Statistics for Informatics
Population
Sample
• Target subject of the study• Composed with individual elements• Finite or Infinite
• If possible, we may investigate all elements of the population.• But, we may select samples from the population.• It is very important how to select samples (Representativeness)
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Representativeness (1)Basic concepts in Statistics for Informatics
Population(== Our goal)
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Representativeness (2)Basic concepts in Statistics for Informatics
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Representativeness (3)Basic concepts in Statistics for Informatics
Sampling bias
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Sampling errorsBasic concepts in Statistics for Informatics
Sampling Error
• It happens because we observe sample, not the whole.
• For example,• Difference between target population and the sample• Faults of the questionnaire.• Non-respose• Interviewer’s error• Deletion from the survey• Data processing error• Etc…
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Fundamental notationBasic concepts in Statistics for Informatics
Population
• Parameters• constants which determine statistical properties of the assumed model
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Measuring central locationBasic concepts in Statistics for Informatics
Mean vs Median
• For a data set, the arithmetic mean, also called the mathematicalexpectation or average, is the central value of a discrete set of numbers:specifically, the sum of the values divided by the number of values.
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Measuring variabilityBasic concepts in Statistics for Informatics
Variability• Range, variance, standard deviation, coefficient of variation
Range
Variance
Coefficient of variation (CV)
Max value – Min value
End of Slide