Issues and activities in authoring ontologiesrobertstevens65
Departmental seminar at Department of Computer Science, university of Birmingham, 6 November, 2014
abstract: Ontologies are complex knowledge representation artefacts used across biomedical sciences, the media and other domains for defining terminologies and providing metadata. Their use is increasing rapidly, but so far, ontology authoring tools have not benefited from empirical research into the ontology authoring process. Understanding how people build ontologies is key to developing tools that can properly support common authoring activities. In this talk I will first present the outcomes of qualative interviews with ontology authors and the issues it reveals. Second, I will present the results of a study that identifies common activity patterns through analysis of the event logs, screen capture and eye-tracking data collected from the popular authoring tool, Protege. Results from this bottom-up investigation suggest that the class hierarchy is the central focus of activity, playing a role beyond simple class representation. We also find that checking how updates to the ontology is hard and performance is hindered by inadequate support in the user interface. From this investigation we propose design guidelines for bulk editing, efficient reasoning and increased situational awareness in ontology authoring.
OBOPedia: An Encyclopaedia of Biology Using OBO OntologiesObopedia swat4ls-20...robertstevens65
A talk on OBOPedia (HTTP://www.obopedia.org.uk) given at Semantic Web Applicaitons and Tools for Life Sciences (SWAT4Ls) 2015 in cambridge, UK December 2015
The state of the nation for ontology developmentrobertstevens65
Invited talk at European Ontology Network (EUON) 2014
Ontologies are now quite big, both literally and metaphorically. They have become central resources in disciplines such as biology, medicine, healthcare and others. Such developments rely on people, tools and methods to deliver ontologies that do the desired job, on-time and on-budget. In this talk I wil ask the question of whether the tools and methods we have are capable of doing what is necessary to deliver robust and maintainable ontologies. To explore this question I will borro from the Capability Maturity Model used to assess the capabilities of institutions to deliver software projects. Instead of institutional assessment, I will bend the CCM to the discipline of ontology engineering. The levels of the CMM range from the ad hoc to one where metrics are used to monitor and adjust ontology development. In this talk I will use some audience participation to gather views on ontology engineering maturity level and then deliver my own view of that maturity.
Properties and Individuals in OWL: Reasoning About Family Historyrobertstevens65
Slides used in an advanced OWL tutorial in 2012. The tutorial is based on family history and uses OWL individuals as a first class citizen in the learning.
Issues and activities in authoring ontologiesrobertstevens65
Departmental seminar at Department of Computer Science, university of Birmingham, 6 November, 2014
abstract: Ontologies are complex knowledge representation artefacts used across biomedical sciences, the media and other domains for defining terminologies and providing metadata. Their use is increasing rapidly, but so far, ontology authoring tools have not benefited from empirical research into the ontology authoring process. Understanding how people build ontologies is key to developing tools that can properly support common authoring activities. In this talk I will first present the outcomes of qualative interviews with ontology authors and the issues it reveals. Second, I will present the results of a study that identifies common activity patterns through analysis of the event logs, screen capture and eye-tracking data collected from the popular authoring tool, Protege. Results from this bottom-up investigation suggest that the class hierarchy is the central focus of activity, playing a role beyond simple class representation. We also find that checking how updates to the ontology is hard and performance is hindered by inadequate support in the user interface. From this investigation we propose design guidelines for bulk editing, efficient reasoning and increased situational awareness in ontology authoring.
OBOPedia: An Encyclopaedia of Biology Using OBO OntologiesObopedia swat4ls-20...robertstevens65
A talk on OBOPedia (HTTP://www.obopedia.org.uk) given at Semantic Web Applicaitons and Tools for Life Sciences (SWAT4Ls) 2015 in cambridge, UK December 2015
The state of the nation for ontology developmentrobertstevens65
Invited talk at European Ontology Network (EUON) 2014
Ontologies are now quite big, both literally and metaphorically. They have become central resources in disciplines such as biology, medicine, healthcare and others. Such developments rely on people, tools and methods to deliver ontologies that do the desired job, on-time and on-budget. In this talk I wil ask the question of whether the tools and methods we have are capable of doing what is necessary to deliver robust and maintainable ontologies. To explore this question I will borro from the Capability Maturity Model used to assess the capabilities of institutions to deliver software projects. Instead of institutional assessment, I will bend the CCM to the discipline of ontology engineering. The levels of the CMM range from the ad hoc to one where metrics are used to monitor and adjust ontology development. In this talk I will use some audience participation to gather views on ontology engineering maturity level and then deliver my own view of that maturity.
Properties and Individuals in OWL: Reasoning About Family Historyrobertstevens65
Slides used in an advanced OWL tutorial in 2012. The tutorial is based on family history and uses OWL individuals as a first class citizen in the learning.
briefly describe enzyme and coenzyme and its role in many orders. Consist of enzyme nomenclature, enzyme part: prosthetic group, metalions, cofactors, and secondary substrate. Describe inhibition action.
"Bacterial metabolism: Fueling life's processes in tiny powerhouses."
Use of bacterial metabolism in biotechnology, biofuels, and other industries
Examples of how bacterial metabolism is harnessed for beneficial purposes
"Metabolism: the sum of chemical reactions in an organism, supporting growth, energy production, and vital functions."
"Bacterial Metabolism and Life: Pervading every aspect of life, shaping ecosystems, and influencing our world."
Bacterial metabolism refers to the collective chemical reactions and processes that occur within bacterial cells, enabling them to maintain life, grow, and reproduce. These metabolic activities involve a complex network of biochemical pathways that facilitate the conversion of nutrients into energy, biomolecules, and essential compounds necessary for bacterial survival.
Metabolic processes in bacteria include catabolic pathways that break down complex molecules (such as sugars) to release energy and anabolic pathways that build complex molecules (such as proteins, nucleic acids) using energy. Bacteria utilize various metabolic strategies based on their energy and carbon sources, including aerobic and anaerobic respiration, fermentation, and photosynthesis in photosynthetic bacteria.
The primary goals of bacterial metabolism are to obtain energy, synthesize necessary cellular components, regulate chemical processes, and adapt to changing environmental conditions. The understanding of bacterial metabolism is crucial for various fields, including medicine, agriculture, biotechnology, and environmental science, as it allows us to develop strategies to combat harmful bacteria, harness their metabolic capabilities for beneficial applications, and study their role in ecological systems.
briefly describe enzyme and coenzyme and its role in many orders. Consist of enzyme nomenclature, enzyme part: prosthetic group, metalions, cofactors, and secondary substrate. Describe inhibition action.
"Bacterial metabolism: Fueling life's processes in tiny powerhouses."
Use of bacterial metabolism in biotechnology, biofuels, and other industries
Examples of how bacterial metabolism is harnessed for beneficial purposes
"Metabolism: the sum of chemical reactions in an organism, supporting growth, energy production, and vital functions."
"Bacterial Metabolism and Life: Pervading every aspect of life, shaping ecosystems, and influencing our world."
Bacterial metabolism refers to the collective chemical reactions and processes that occur within bacterial cells, enabling them to maintain life, grow, and reproduce. These metabolic activities involve a complex network of biochemical pathways that facilitate the conversion of nutrients into energy, biomolecules, and essential compounds necessary for bacterial survival.
Metabolic processes in bacteria include catabolic pathways that break down complex molecules (such as sugars) to release energy and anabolic pathways that build complex molecules (such as proteins, nucleic acids) using energy. Bacteria utilize various metabolic strategies based on their energy and carbon sources, including aerobic and anaerobic respiration, fermentation, and photosynthesis in photosynthetic bacteria.
The primary goals of bacterial metabolism are to obtain energy, synthesize necessary cellular components, regulate chemical processes, and adapt to changing environmental conditions. The understanding of bacterial metabolism is crucial for various fields, including medicine, agriculture, biotechnology, and environmental science, as it allows us to develop strategies to combat harmful bacteria, harness their metabolic capabilities for beneficial applications, and study their role in ecological systems.
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...University of Maribor
Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
Cancer cell metabolism: special Reference to Lactate Pathway
The Pragmatics and Formality of Authoring OntologiesOdsl 2016
1. Formality and Pragmatics in
Authoring Ontologies
Robert Stevens
ODLS 2016
School of Computer Science
The University of Manchester
Manchester
United Kingdom
M13 9PL
Robert.stevens@manchester.ac.uk
2. Acknowledgements
• On-going work with Phil Lord on normalising
the Gene Ontology
• The Gene Ontology folk for making GO
• Nico Matentzoglu for my slides
• Mercedes Casteleiro for numbers
3. Formality and Pragmatics
• Formality: Acting strictly according to
procedure or rules
– Ontological formality
– Representational formality
• Pragmatics: Behaviour driven by practical
consequences rather than dogma
• There’s a tension between the two
6. What is Molecular Function in GO?
• Describes “function”…?
GO:0003674
molecular_function
Elemental activities, such as catalysis or
binding, describing the actions of a
gene product at the molecular level. A
given gene product may exhibit one
or more molecular functions.
7. Motivation
• Is GO’s molecular function ontology really
function, “little” processes or both?
• Documented as a function
• Sometimes looks like a process
• Sometimes treated like a process
• Confusion of thing with a function and the
function
• This can make modelling harder than it need be
8. A Couple of Observations
• Pragmatically, we commit to GO – it’s the only
show in town and it works
• There’s a lot of chemicals around in GO MF
• We are biochemistry….!
• Probably few functions – strip out all the “non-
function” stuff and see what’s left
• Then we can look at the ontological nature of GO
MF
• Also, re-create in a more sustainable form
11. There are several dimensions of
classification here
• The amino acids themselves – a chemical dimension
• The size of the amino acids side chain
• The charge on the side chain
• The polarity of the side chain
• The hydrophobicity of the side chain
• We can normalise these into separate hierarchies then put
them back together again
• Our goal is to put entities into separate trees all formed on
the same basis
• Size only talks about size; amino acid only talks about
chemical composition (based on an alpha-carbon with an
amino and carboxylic acid group);and so onof classification
13
13. The process
• Hand-crafted ontologies with a polyhierarchy
are “tangled”
• Usually axiomatically lean
• We classify along one axis and use
“restrictions” to other modules to capture
other axes
• Then re-build the polyhierarchy using the
axiomatically rich ontology
15
14. “Pulling out” dimensions
• Each separate tree must be the same kind of
thing
• We don’t mix continuants, processes,
qualities, etc
• We don’t mix our classification by, for
instance, structure and then charge
• We do that compositionally via defined classes
and automated reasoners
16
15. The amino acid pattern
17
Class: AminoAcid
SubClassOf:
hasSize some Size,
hasPolarity some Polar,
hasCharge some Charge,
hasHydrophobicity some Hydrophobicity
16. An amino acid
18
Class: Lysine
SubClassOf:
AminoAcid,
hasSize some Large,
hasCharge some Positive,
hasPolarity some Polar,
hasHydrophobicity some Hydrophilic
17. Rebuilding the hierarchy
• Class: LargeAminoAcid
– EquivalentTo: AminoAcid
• and hasSize some Large
• Class: PositiveAminoAcid
– EquivalentTo: AminoAcid
– and hasCharge some Positive
• Class: LargePositiveAminoAcid
– EquivalentTo: LargeAminoAcid and PositiveAminoAcid
19
19. Other Ontology Topics as
Factors in GO MF
molecular
function
chemical
chemical
role
reaction
biological
process
cellular
component
cell
protein
sequence
40-60% of terms
mention chemicals
21. Binding
• ~2k terms in the binding bit of GO MF
• Remove the chemicals
• Leaves “binding”
• There is a function “to bind”
• There is a process of binding”
• Linguistically – an infinitive and a
gerund/nominalised verb
22. More “to bind” Functions?
• “to bind” is the basic function
• Specialise to to bind covalently, to bind via
hydrogen, to bind electrostatically
but these are built compositionally with
reference to other ontologies
23. Chemorepellant - chemoattractant
activity
GO:0042056
chemoattractant activity
Providing the environmental signal that
initiates the directed movement of a
motile cell or organism towards a
higher concentration of that signal.
GO:0045499
chemorepellent activity
Providing the environmental signal that
initiates the directed movement of a
motile cell or organism towards a
lower concentration of that signal.
To diffuse
26. Distinctions with no (practical)
difference
• “Distinction without a difference” – making a
distinction where none exists
• Distinctions may exist, but does one need to
make them?
• Does a distinction make a practical difference
to the use case in hand?
• Make no distinction unless it makes a
difference
• Beware of consistency…
30. Some patterns
• hasRealisableEntity some (to_bind and
realisedIn only (binding and hasInput some
chemical)))
• Add “playsrole some role” for a chemical role
like drug
• hasRealisableEntity some (to_catalyse and
realisedIn only (catalysis and hasInput some
chemical and hasOutput some chemical))
31. Actually doing it
• Programmatically using Tawny-OWL
• Asserted tree of molecular realisables and
molecular processes
• Defined classes for the actual terms
• May have to restrict to OWL EL for practical
reasons
• We shall see…
32. Strategies for Defined Classes
• Total post co-ordination
• Total pre co-ordination
• Pre co-ordinate those classes that have been
used in annotation
33. How many GO MF terms are used?
Annotation file
Homo sapiens: Canonical
accessions from UniProt
(goa_human.gaf.gz)
Unfiltered GOA UniProt gene
association file
(goa_uniprot_all.gaf.gz)
Total number of GO-
UniProt annotations 354 515 ~ 354K 294 208 149 ~ 294M
Unique UniProt IDs 19 055 ~ 19K 45 968 890 ~ 46M
Unique active Molecular
Function classes 3 947 ~ 4K 7 521 ~ 7K
Unique active Molecular
Function classes used
more than 5 times
1 313 ~ 1K
34. What have we found?
• Very few functions
• … and some look dispositional
• It looks like physics
• Most functions involve binding – makes sense
• We separate realisables and processes
• We live with a bit of “replication”
• With molecular processes, do we need molecular
funtion?
• WE change the upper reaches of GO MF, but…
• Does it make any practical difference?
35. Formality
• Ontological formality
• Making the right distinctions drives consistent
use of relationships
• Facilitates the kind of analysis we’ve done
• Can also be a barrier to progress
• Representational formality
• Knowing what is being said is useful
• Allows clean interpretation
• Enables useful reasoning
36. Pragmatic Decisions
• Commit enough to achieve goals
• If re-using take on the commitments of that ontology
– If using OBO commit to OBO
– If what you’re using uses something with which you
disagree – get over it
• Axiom pragmatics
• Don’t represent that which isn’t needed
• Truth and beauty
• A counsel of perfection is a counsel of despair
• I’d make “gene product” explicit
Editor's Notes
Informal definitions of the words formality and pragmatics
I build ontology based applicationis and pragmatics come into play
I like formality (up to a point) but I’d prefer an applicationi that does something over a formal ontology that is not usable – both is great, but I scarifice formality first
1)
#Slide with molecular function title
#add textbox with number of terms
#URL: http://geneontology.org/
D-alanyl carrier activity
acetylcholine receptor regulator activity
antioxidant activity
binding
calcium channel regulator activity
catalytic activity
channel regulator activity
chemoattractant activity
chemorepellent activity
core DNA-dependent RNA polymerase binding promoter specificity activity
electron carrier activity
enzyme regulator activity
guanyl-nucleotide exchange factor activity
metallochaperone activity
mitochondrial RNA polymerase binding promoter specificity activity
molecular function regulator
molecular function regulator
molecular transducer activity
morphogen activity
negative regulation of molecular function
neurotransmitter receptor regulator activity
nucleic acid binding transcription factor activity
nutrient reservoir activity
positive regulation of molecular function
protein tag
receptor regulator activity
regulation of molecular function
signal transducer activity
structural molecule activity
transcription factor activity, core RNA polymerase I binding
transcription factor activity, core RNA polymerase II binding
transcription factor activity, core RNA polymerase III binding
transcription factor activity, core RNA polymerase binding
transcription factor activity, protein binding
transcription factor activity, transcription factor binding
translation regulator activity
transporter activity
title: GO Molecular function
1. molecular_function (GO:0003674)
"Elemental activities, such as catalysis or binding, describing the actions of a gene product at the molecular level. A given gene product may exhibit one
or more molecular functions."
- 1. above in a box at the top of the slide with a text box below into which I can put bullets. the first bullet is
* Describes "function"....?
first slide is a tangled hiearchy (title "Normalisation 1"
"Vehicle" at the top
the leaves are:
fast red sports car
fast green sports car
red lorry
slow yellow lorry
green van
fast red motor cycle
black estate car
green saloon car
red estate car
Then some intermedate, "defined classes" such as:
red vehicle green vehicle
fast red car
red car
and any you can think of andmake it tangled
second slide (title "Normalisation 2")
separate out a set of hierarchies
Vehicle
colour
speed
style
and if you can fit it on, an axiom pattern of
Class: Vehicle
SubClassOf:
hasColour some Colour
hasStyle some Style
hasSpeed some Speed
Normalisation; a paper from Alan Rector (2003)
This pulling out of non-function aspects of GO MF I not complete
Most aspects have OBO support
Not electron and energy
title: Chemorepellant - chemoattractant activity
below, 1 and 2 are some kind of box with the GO term and Id as some form of title with the definition below. this links down to a blob containing 3.
1. chemoattractant activity (GO:0042056)
Providing the environmental signal that initiates the directed movement of a motile cell or organism towards a higher concentration of that signal.
2.chemorepellent activity (GO:0045499)
Providing the environmental signal that initiates the directed movement of a motile cell or organism towards a lower concentration of that signal.
3. both linking down to a blob containing "To diffuse"
RealizableEntity
Some of these functions l look dispoitional
To store, to diffuse and to structurally maintain
Lots of these “functyions” als also imply bidning
This is not a surprise as some binding must happen for anything to happen(as-subclasses
ToCatalyse
:comment "To reduce the activation energy of a reaction, enabling it to go
faster.")
(defclass ToBind
:comment "To interact tightly with another entity, longer than transiently,
such that separating the entity requires significant energy. ToBind
functions are often transitive; A has a function ToBind B, then vice versa
is also true.")
(defclass ToMark
:comment "To bind between this entity X, and another entity Y, so that
a third entity Z can also be bound, and thereby interact with Y."
:super ToBind))
;; #+end_src
(defclass ToStore
:comment "To contain a substance for later use.")
(defclass ToDiffuse
:comment "To spread outward from a single point as a result of Brownian
motion.")
(defclass ToTransport
:comment "To enable the movement of an entity in a directed manner.")
(defclass ToMaintainIntegrity
:comment "To keep the same structure, shape or organisation despite
physical forces, either in compression or in extension.")
(defclass ToProtect
:comment "To prevent an event occuring to this or another entity.")
(defclass ToModulate
:comment "To alter the strength or quantity of some other realisable entity.")
(defclass ToRegulate
:comment "To modulate in a directed manner, as part of a feedback loop."
:super ToModulate)
(defclass ToTransduce
:comment "To change energy from one form to another.")
Talk about Mungall et al’s normalisation of GO
Partial; not down to the bare functions
Intersting point around ribose sugars