PIMS Project Glossary
Process impact: This file as a
dictionary of terms defined as they are used during the project.
Writing out the definitions of terms and acronyms here helps keep
other documents more concise and precise. A shared glossary helps
prevent misunderstandings and makes it easier for new team members to
be productive.
This is a glossary of terms used in the development process for the project. It includes standard IT terms and some custom ones. For biological terms, see the documentation of the data model.
Project-specific Terms
TIPs:
- Define HTML anchors on your terms with id="TERMNAME" so that
other documents can link to the definition of specific terms.
- If there is any question about the meaning of a term, note it
here. If someone (e.g., the customer) gave you a definition to
use, note that here too. If something is best defined by using a
hyperlink to another document or website, include a hyperlink in
the definition.
- If a term was used in the past, but is no longer going to be
used, you should keep it in the list, mark it as "deprecated", and
link to the term or terms that replace it. E.g., deprecated
standard term bug.
- Define only project-specific terms, or ones that a new team
member would not know. Don't define standard textbook terms that
can be easily found elsewhere.
- This glossary can serve as simple domain model or data
dictionary. You can define important data objects by describing
their meaning and key attributes. For example, see student and GPA.
- Blueprint component
- A 'wish target', domain or fragment of a 'wish target', DNA, RNA, poly- or
olio-saccharides or a small molecule ligand or co-factor.
Part of an Experiment Blueprint
- Crystallisation space
- The physico-chemical and protein-specific parameters which define the
conditions in a crystallisation well
may include:
- pH
- temperature
- concentration of various salts, precipitants, buffers, additives etc.
- drop size
- protein concentration
- presence/absence of co-factors or ligands
These can be thought of as the co-ordinates in a multi-dimensional space.
In a typical crystallisation experiment, the number of dimensions will
be approximately 100.
The probability of a crystallisation well yielding crystals, for a particular
protein will vary with movement through this space.
- Experiment Blueprint (the name may be changed)
- The term Experiment Blueprint is a description of a clearly defined experimental
objective i.e what you plan to work on.
- It describes any particular combination of one or more 'wish targets', domains or
fragments of 'wish targets', DNA, RNA, poly- or olio-saccharides or any small molecule
ligand or co-factor that you intend to study.
Each of these is defined as a Blueprint component.
- Examples of an Experiment Blueprint might be:
a protein, a protein-DNA complex, a multi-protein complex or a protein comlexed with a
ligand or co-factor.
- In addition, many Experiment Blueprints can de defined from a single 'wish target'
illustrating the fact that different domains or fragments of the 'wish target' may be
studied in various contexts.
For example: a given protein may have more than one distinct domains such as a kinase
with catalytic and regulatory domains.
You may intend to study different aspects of the protein and so separate Experiment
Blueprints might be:
- the full length protein
- the kinase domain
- the regulatory domain
- a complex between the two domains
- a complex including a substrate
- In addition, an Experiment Blueprint might contain Blueprint components defined
from separate Experiment Blueprints.
For example: an Experiment Blueprint, called AB1, describes an oligomeric protein AB
with two subunits A and B.
This Experiment Blueprint will, therefore contain two Blueprint components A' and B',
defined from thier respective 'wish targets' A and B.
A different Experiment Blueprint, AB2, describes the AB complex with a co-factor C bound.
In this case, there might be three Blueprint components A', B' and C' where C' is
defined from a separate Experiment Blueprint C.
- Express (exprimer)
- To make protein from a gene.
- Extinction Coefficient
- The extinction coefficient (E) of a protein is an indicator of how
much light it absorbs at a particular wavelength.
The molar extinction coefficient is a measure of the amount of light
absorbed by a 1M solution in a pathlength of 1cm at a given wavelength.
This is a useful parameter for determining the concentration of a protein
for example, during its purification.
The (molar) extinction coefficient of a protein can be estimated from a
knowledge of its amino acid composition. The calculation is based on the
number of tyrosine, tryptophan and cystine residues it contains using the
known molar extinction coefficients of these residues.
The calculation forms part of the ExPASy
ProtParam tool
E (protein) = no. Tyr x E (Tyr) + no. Trp x E(Trp) + no. Cys x E(Cys)
The absorbance of the protein can then be calclated:
Absorbance(protein) = E(protein) / Molecular weight
- GMO
- Genetically Modified Organism. A target protein is produced by adding the gene for it to a suitable organism, often E.Coli.
- Homologous sequence
- Protein, or nucleotide sequences are likely to be homologous if they show
a "significant" level of sequence similarity. Truely homologous
sequences are related by divergence from a common ancestor gene. Sequence
homologues can be of two types:
(i) where homologues exist in different species they are known as orthologues.
e.g. the α-globin genes in mouse and human are orthologues.
(ii) paralogues are homologous genes in within a single species. e.g. the
α- and β- globin genes in mouse are paralogues
- Lab book (le cahier de manipulation)
- A scientst's personal record of experiments planned and performed.
The traditional way of managing laboratory information.
- LIMS
- Laboratory Information Management System
- Molecular Component
- PIMS defines a pure component with a known chemical structure, such as
'Sodium chloride', as a Molecular Component.
Restriction enzymes, constructs and primers are also examples of Molecular
Components with additional characteristics.
Molecular Components are distinct from other components classified as
'Substance' Cell' and 'Composite'.
- Optimisation
- A further screening experiment, after an initial screening has indicated the approximate conditions for success.
The screen used for optimisation will be customised
in the light of the results of the screening experiment.
How best to do this is a topic for research.
Analysis of the records of past experiments (data mining) will facilitate this research.
- Plate (la plaque)
- A holder with multiple wells (usually 24, 96, or 384), each capable of containing a sample.
- Protocol (le protocole)
- A procedure for carrying out an experiment.
- Rack (l'etagere)
- A holder capable of containing several plates.
- Refinement
- See optimisation.
- Sample (l'echantillon)
- An aliquot: often some liquid in a container.
May have known SampleComponents (des composants) indicating its composition.
Most experiments create new samples.
- Scale-up
- v. or n. To perform an experiment in bulk, after the optimal conditions
have been determined by a screening experiment.
- Scientific Goal
- The scientific goals of the project are the areas where PIMS can help scientists manage experimental and target information. They represent a means of grouping use cases based on perceived project needs, as defined in the project proposal and from requirements gathering. For certain scientific goals, the use of PIMS might influence laboratory practice. For example, the introduction of barcoding to facilitate sample tracking.
- A scientific goal is what Alistair Cockburn calls a strategic scope, summary goal.
- Screen
- i. To perform a screening experiment.
- n. A range of reagents (or samples mixed from standard reagents)
prepared for use in a screening experiment, one for each constituent experiment.
- Screening Experiment
- There are situations where the appropriate reagents and/or conditions
to use for a particular experiment have not been established. To resolve
this problem, it is necessary to perform one or more experiments
simultaneously, where the conditions and/or reagents are varied
systematically in order to define a range of favourable combinations.
The outcome of such a primary screen will help to define a narrower range
of conditions for either optimisation or
scale-up.