Disease Informatics: Terms and Jargon to begin with

1. Disease Informatics: Terms and Jargon to begin with R. P. Deolankar

2. General Terms

3. 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 • The inferences drawn from earlier work provides the basis for projected work

4. 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

5. 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 Hypothesis • 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 Postulation • Hypothesis that cannot be tested and hence taken for granted • A statement as the basis of a theory

6. (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 Precautions • Keeping a written list of multiple hypotheses is necessary • Difficult to test • Vacillation is preferable to the premature rush to a false conclusion

7. Thomas Chrowder ChamberlinAuthor of Method of Multiple Working Hypotheses

8. 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

9. 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

10. 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

11. Biomarker • 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.

12. 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

13. 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

14. 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

15. 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

16. Book by Rothman and Greenland

17. 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

18. Algorithm • A precise rule or set of rules • A sequence of instructions • Specify how to solve some problem

19. Metathesaurus • 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

20. SNOMED CT and SNOMED RT • SNOMED: Sytematized NOMencalture of MEDicine • CT for Clinical Terms • RT for reference terminology

21. 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

22. 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)

23. Semantic Network • Knowledge diagram with graphic notation • Looks like flow chart • Contains patterns of interconnected nodes and arcs

24. 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

25. Genetic terminology

26. Essential genes • Genes required for growth to a fertile adult • Essential for viability

27. Housekeeping genes • Involved in basic functions needed for the sustenance of the cell • Constitutively expressed • They are always turned ON e.g. actin

28. 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

29. 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)

30. Epigenetic • 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

31. 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.

32. 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

33. Orthologs: orthologous genes • Orthologous genes: genes that have evolved directly from an ancestral gene • This is in contrast to paralogous genes

34. Interlogs • 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

35. Interologous Interaction Database • Web-accessible database to facilitate experimentation and integrated computational analysis with model organism Protein-Protein-Interaction networks

36. Regulogs • 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

37. Translational medicine: ("Bench to bedside" research) • Clinical Research orienting interaction between basic research and clinical medicine, particularly in clinical trials

38. 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

39. Predictive medicine • Identifying biological markers in order to enroll individuals at high risk for developing a disease in special early detection trials

40. Meta-analysis • In statistics, a meta-analysis combines the results of several studies that address a set of related research hypotheses

41. 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

42. Omics terms

43. Genomics • The branch of genetics that studies organisms in terms of their genomes (their full DNA sequences)

44. Pharmacogenomics • 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

45. Nutrigenomics • Study of molecular relationships between nutrition and the response of genes • Personalized nutrition based on genotype

46. Phenomics • Field of study concerned with the characterization of phenotypes • Phenotypes arise via the interaction of the genome with the environment

47. Transcriptome and transcriptomics Transcriptome • The complete set of RNA products (mRNAs, or transcripts in a particular tissue at a particular time) that can be produced from the genome Transcriptomics • The study of the transcriptome

48. 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

49. 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