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Disease Informatics: Terms and Jargon to begin with. R. P. Deolankar. General Terms. Data and Information. Data Numbers Words Images Information is derived from the data Information It is the knowledge derived from analysis of the data Inferences can be drawn from information

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Disease Informatics: Terms and Jargon to begin with

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data and information
Data and Information


  • Numbers
  • Words
  • Images
  • Information is derived from the data


  • It is the knowledge derived from analysis of the data
  • Inferences can be drawn from information
  • The inferences drawn from earlier work provides the basis for projected work
target information and information gap
Target information and Information gap

Target information

  • Information which is required but not available
  • The information goal intended to be attained

Information gap

  • Total information required to hit the information target minus available information
research question and hypothesis
Research question and Hypothesis

Research question

  • This is the question, if answered, could eliminate the information gap
  • The cycle of setting the information target, locating the information gap and raising new research questions is the part of process of research


  • This is a tentative answer to the research question
  • The hypothesis is tested by performing the experiment
  • After testing, hypothesis is either accepted or rejected


  • Hypothesis that cannot be tested and hence taken for granted
  • A statement as the basis of a theory
disease phenomenon is the result of several causes not just one multiple hypotheses
(Disease phenomenon is the result of several causes, not just one)Multiple hypotheses
  • More effective way of organizing research
  • Provides stimulus for study and fact-finding
  • See the interaction of the several causes
  • Promotes much greater thoroughness
  • Leads to lines of inquiry that we might otherwise overlook
  • Avoids the pitfall of accepting weak or flawed evidence for one hypothesis when another provides a more elegant solution


  • Keeping a written list of multiple hypotheses is necessary
  • Difficult to test
  • Vacillation is preferable to the premature rush to a false conclusion
what is ontology
What is ontology?
  • Incomplete information gives rise to speculation
  • Hierarchical structuring of speculations about things within a particular domain is ontology
  • Ontology is the statement of a logical theory
disease ontology
Disease Ontology
  • Controlled Medical Vocabulary
  • Facilitate mapping of diseases and associated conditions to codes such as ICD, SNOMED and others
  • Disease Ontology (DO) is developed at the Bioinformatics Core Facility in collaboration with the NuGene Project at the Center for Genetic Medicine, USA
clinical event
Clinical event
  • Clinical: related to the health or disease
  • Event: something that happens at a given place and time
  • Depicted at both the ends of “cause and effect diagram”
  • Link of a Disease Causal Chain
  • Backend event: Event occurring earlier to the focused event
  • Frontend event: Event occurring next to the focused event
  • Indicator of event of health / disease / clinical history
  • Usually biochemical metabolite
  • Indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention.
disease causal chain
Disease Causal Chain
  • Diagram depicting chain or net
  • Links of chain are events
  • Progress from one event to other is shown by “Cause and effect” diagram
  • Journey from one event to the other is driven by factors
model organism
Model organism
  • Animal model in study of diseases
  • Discoveries made in the animal model provides insight into the human disease study
  • Studies include pathogenesis, potential causes and treatments of diseases
  • Basis: common descent of all living organisms, and the conservation of metabolic and developmental pathways and genetic material over the course of evolution
  • Research performed using poor quality animals could be misguiding
component cause
Component cause
  • Belief in one cause one effect is a major error in disease investigation
  • Single component cause does not result in disease
  • Virus is a component cause in a viral disease
  • Subset of sufficient causes does not result in a disease but could predispose
  • Most causes of interest to the epidemiologist are actually components of a sufficient cause
sufficient cause
Sufficient cause
  • Sufficient causes are constellation of component causes that could result in a disease
  • Factors contributing susceptibility to virus are also component causes of viral disease
  • Disease can originate from either of several different sufficient causes
ncl 60 lines
NCL-60 lines
  • Cell lines for anticancer drug screening
  • Developed by the National Cancer Institute, Maryland, USA
  • Reflect diverse cell lineages [lung, renal, colorectal, ovarian, breast, prostate, central nervous system, melanoma, and hematological malignancies]
  • Such panels could be prepared for other diseases also
  • A precise rule or set of rules
  • A sequence of instructions
  • Specify how to solve some problem
  • Vocabulary for information retrival
  • Integrated from synonyms and antonyms for common words and phrases (thesauri)
  • e.g. Unified Medical Language System to integrate into a single system the terminology of the biomedical sciences
snomed ct and snomed rt
  • SNOMED: Sytematized NOMencalture of MEDicine
  • CT for Clinical Terms
  • RT for reference terminology
umls unified medical language system
UMLS: Unified Medical Language System
  • UMLS is a metathesaurus
  • Developed by the National Library of Medicine (NLM)
  • Contains Knowledge Sources (databases) and associated software tools (programs)
  • Useful for developers of computer system
uml unified modeling language not to be confused with umls
UML: Unified Modeling Language Not to be confused with UMLS
  • A standardized general-purpose modeling language in the field of software engineering
  • UML includes a set of graphical notation techniques
  • Creates abstract models of specific systems
  • Diagrams: structure (Class, Component, Composite structure, Deployment, Object and Package diagrams), behavior (Activity, State and Use case) and interaction (Communication, Interaction overview, Sequence and Timing)
semantic network
Semantic Network
  • Knowledge diagram with graphic notation
  • Looks like flow chart
  • Contains patterns of interconnected nodes and arcs
specialist lexicon
  • SPECIALIST is the name of Natural Language Processing (NLP) System
  • Lexicon (dictionary like document) developed using SPECIALIST is SPECIALIST lexicon
  • Vocabulary encompassing English and biomedical terminology
  • The lexicon entry for each word or term records the syntactic, morphological, and orthographic information needed by the SPECIALIST NLP System
essential genes
Essential genes
  • Genes required for growth to a fertile adult
  • Essential for viability
housekeeping genes
Housekeeping genes
  • Involved in basic functions needed for the sustenance of the cell
  • Constitutively expressed
  • They are always turned ON e.g. actin
disease associated genes
Disease-associated genes
  • Alleles carrying particular DNA sequences associated with the presence of disease
  • e.g. Gene UNC-93B deficiency as a genetic etiology of Herpes Simplex Encephalitis
  • Lack of Stat1 interferon signaling gene enhances pathogenesis of a viral disease
gene ontology go
Gene Ontology (GO)
  • The Gene Ontology (GO) is a project
  • Provides a controlled vocabulary to describe gene and gene product attributes in any organism
  • (the molecular function of gene products; their role in multi-step biological processes; and their localization to cellular components)
  • Relating to, being, or involving a modification in gene expression
  • It is independent of the DNA sequence of a gene
  • DNA methylation, chromatin remodeling, transcription factors etc
paralogs paralogous genes
Paralogs: Paralogous genes
  • Two genes or clusters of genes at different chromosomal locations in the same organism
  • Have structural similarities indicating that they derived from a common ancestral gene
  • Have diverged from the parent copy by mutation and selection or drift.
homologs homologous genes
Homologs: Homologous genes
  • Homologs: Having the same relative position, value, or structure, something (as a chemical compound or a chromosome) that is homologous
  • Homologous sequences are of two types: orthologous and paralogous
orthologs orthologous genes
Orthologs: orthologous genes
  • Orthologous genes: genes that have evolved directly from an ancestral gene
  • This is in contrast to paralogous genes
  • Suppose protein molecules (from one species of animal say human) A and B interact; homologous protein molecules (from another species of animal say dog) A’ and B’ also interact, then interlogs are:
  • Resembling pair of protein-protein interactions (e.g. A-B and A'-B')
  • Can be observed parallelly in two different organisms
interologous interaction database
Interologous Interaction Database
  • Web-accessible database to facilitate experimentation and integrated computational analysis with model organism Protein-Protein-Interaction networks
  • Sets of co-regulated genes for which the regulatory sequence has been conserved across multiple organisms
  • The quantitative method assigns a confidence score to each predicted regulog member on the basis of the degree of conservation of protein sequence and regulatory mechanisms
translational medicine bench to bedside research
Translational medicine: ("Bench to bedside" research)
  • Clinical Research orienting interaction between basic research and clinical medicine, particularly in clinical trials
systems biology
Systems biology
  • Relatively new biological study field
  • Focuses on the systematic study of complex interactions in biological systems
  • Uses a new perspective (integration instead of reduction) to study complex interactions
predictive medicine
Predictive medicine
  • Identifying biological markers in order to enroll individuals at high risk for developing a disease in special early detection trials
meta analysis
  • In statistics, a meta-analysis combines the results of several studies that address a set of related research hypotheses
bayesian approach
Bayesian approach
  • Statistical approach based on Bayes' theorem
  • Application of Baye’s theorem: Bayes' theorem can be applied to calculate the probability that a positive medical test result of a disease is a false positive hence retesting is planned
  • Bayes' theorem can be also be applied to calculate the probability of a false negative
  • The branch of genetics that studies organisms in terms of their genomes (their full DNA sequences)
  • Study of how an individual's genetic inheritance affects the body's response to drugs
  • Tailor-made for individuals and adapted to each person's own genetic makeup
  • Greater efficacy and safety
  • Environment, diet, age, lifestyle, and state of health all can influence a person's response to medicines
  • Study of molecular relationships between nutrition and the response of genes
  • Personalized nutrition based on genotype
  • Field of study concerned with the characterization of phenotypes
  • Phenotypes arise via the interaction of the genome with the environment
transcriptome and transcriptomics
Transcriptome and transcriptomics


  • The complete set of RNA products (mRNAs, or transcripts in a particular tissue at a particular time) that can be produced from the genome


  • The study of the transcriptome
proteome and proteomics
Proteome and proteomics
  • Proteome
  • PROTEin complement to a genOME
  • Proteomics
  • The qualitative and quantitative comparison of proteomes
  • The comparison under different conditions to further unravel biological processes
metabolome and metabolomics
Metabolome and Metabolomics
  • Metabolome
  • It represents the collection of all metabolites in a biological organism, which are the end products of its gene expression
  • Metabolomics
  • Study of metabolome under different conditions