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Software Engineering 2012, 2(4): 147-159
DOI: 10.5923/j.se.20120204.08
Formal UML Modelling of Isotopo, Bioinformatical
Software for Mass Isotopomers Distribution Analysis
Zeeshan Ahmed*, Saman Majeed , Thomas Dandekar
Department of Bioinformatics, Biocenter, University of Wuerzburg, Germany
Abstract Mass isotopomer distribution analysis (MIDA) is a technique towards the measurement of amalgamation of
polymers by involving the process of quantification of relative abundances of molecular species with mass spectrometry.
The objective of this research is to study metabolic isotopes to quantify the fraction of metabolites of interest in the mixture
typically by tracing isotopes. Estimating mass isotopomers distribution from spectral data is an extension of the quantitative
mass spectrometric method to a multi component mixture analysis. Focusing on identifying the quantity of population of
labelled isotopomers for resolving the exact rate of synthesized fractions present in the mixture and metabolic experimental
data management, a new software application named “Isotopo” is proposed and designed. Isotopo is an application with
proposed abilities of performing quantitative mass spectrometry to readily mixtures of materials labelled with stable
isotopes. This can be very important for both biomedicine and biochemistry. Most recent version of Isotopo will have the
ability of processing experimental isotopomers data and estimating mass values and relative intensities. Using formal
mathematical algorithms which generate an appropriate set of linear simultaneous equations, it will predict natural
abundance values, relative isotopic abundance values and fractional molar abundance values for each fragment from
labelled substance based experimental data elements. Using Isotopo it will also possible to process data sets with multiple
data entries up to three actual intensity values against one mass to charge ratio values, estimate absolute enrichment, mean
and standard deviation of both natural and relative isotopic abundances. Isotopo will also provide the standardization of
experimental data with a file based record keeping system for experimental data manipulation and management. In this
paper justifying the need of a new software application, we also present the followed V-Model, formal UML designs
(including use case, data flow, flow chart, system sequence, component and class diagrams), and designed graphical user
interface of Isotopo.
Keywords Bioinformatics, Design, Human Computer Interaction (HCI), Mockup, Mass Isotopomers Distribution
Analysis (MIDA), Metabolic Flux Analysis (MFA), Unified Modelling Language (UML)
1. Introduction
Bioinformatics is one of the recently introduced and
highly contributing fields towards empirical, computational
and complex data analysis with the involvement of
probability, statistics, mathematics and informatics (e.g.[1]).
It is providing heavy experimental data management and
manipulation using relational database management system
(e.g.[2],[3]) and globalizing data at web using grid[4] and
semantic web[5] technologies etc. Bioinformatics has
already challenged to explore several natural sciences areas
e.g. metabolic network analysis and (re)construction,
automation of genome annotation, protein structure
determination etc., and provided values to the field of
biology (& related) but still lots of areas need to be targeted
and improved.
* Corresponding author: Zeeshan Ahmed
zeeshan.ahmed@uni-wuerzburg.de (Zeeshan Ahmed)
Published online at http://journal.sapub.org/se
Copyright © 2012 Scientific & Academic Publishing. All Rights Reserved
The objective of this research is to study metabolic
isotope to quantify the fraction of metabolites of interest in
the mixture typically by tracing isotopes. Mass isotopomer
distribution analysis (MIDA) measures the mixtures of
polymers (e.g. lipids, carbohydrates and proteins) by
quantifying relative abundances of molecular species with
Mass Spectrometry (MS; a systematic technique to measure
the mass-to-charge ratio values of charged particles)[6]. MS
converts individual molecules into ions to direct them in
magnetic fields using Mass Spectrometer[7]. During
GC-MS, at first a mixture of compounds is inserted into the
GC to vaporize using a heated chamber to separate
compounds for MS analysis, by travelling into GC column.
A chromatogram is drawn, representing each compound
with its peak. All Mass Spectrometers consists of three
main sections: Ionizer, Ion Analyzer and Detector[8]
(Figure 1). Electron impact ionization is performed by
Ionizer with a gas chromatograph using a high-energy
electron beam to collect molecular ions and fragments. Ion
Analyzer accelerates obtained molecular ions and fragments
148 Zeeshan Ahmed et al.: Formal UML Modelling of Isotopo, Bioinformatical Software
for Mass Isotopomers Distribution Analysis
by manoeuvring the charged particles using mass
spectrometer, eliminating uncharged molecular ions and
fragments. The job of the Detector is to generate an
electronic signal at every ion hit. During this process mass
analyser classifies the ions with respect to the mass to
charge ratio values and detector extracts the abundance
values of each mass to charge ratio value.
Figure Legend. GC-MS process consists of three main steps: Ionizer,
Ion Analyzer and Detector, with supporting activities: sample source input,
gas phase ions production and m/z separation (Ionizer), ion sorting, m/z
separation and fragment (Ion Analyzer), and ion detection, generated data
for further computation analysis (Detector)
Figure 1. Gas Chromatography Mass Spectrometry Process (GC-MS)
Estimating mass isotopomers distribution from spectral
data is an extension of the quantitative mass spectrometric
method to a multi component mixture analysis[9]. Mass
spectrometric analysis describes relative abundances
quantitatively based on combinatorial probabilities. It is
essential to identify the quantity of the labelled isotopomer
population to resolve the exact amount present in the
mixture. The exact identification of the number of labelled
isotopomers in a mixed population of molecules is a
mathematical challenge. Different calculation algorithms
have already been proposed and published for MIDA with
overlapping solutions in successive iterations[10]. These
generate identical results. A formal mathematical algorithm
generates an appropriate set of linear simultaneous
equations and finds their solutions, for the calculation of
both natural isotope abundances and relative isotope
abundances.
Some software applications do exists for mass
isotopomers distribution analysis and metabolic modelling.
As it is a broad field contributing towards the development
of understanding between complex interactions, control and
regulation of metabolic networks. Metabolic flux analysis is
one of the key methods of metabolic modelling[11]. We
(our group) have also developed some computational
software applications (e.g. Isotopo, Yana[12],
Yanasquare[12] and Yanavergence[13] etc.) for complex
pathway analysis and isotopic distribution prediction[14].
Most importantly there is an existing solution provided by
Priv. Doz. Wolfgang Eisenreich’s group at Institute of
Biochemistry Technical University Munich Germany,
implementing the similar methodology but with completely
different way of development and usage; in the form of a
Microsoft excel macro. To process experimental metabolite
data using developed macro, user at first needs to store
experimental data in Microsoft excel sheets in a particular
user unfriendly way and has to set many paths and
configurations. To meet the aforementioned goals of the
research, a new software application is needed to be
designed and developed.
This manuscript presents research conducted to establish
a user friendly platform for mass isotopomer distribution
analysis (MIDA), another technique that enables the
determination of metabolic fluxes on the basis of labelling
experiments using 13C-enriched precursors. A new
software application named ‘Isotopo’ is proposed and
designed with facile data management and robustness to
quantify the populations of isotopomers in mixtures of
13C-labelled amino acids. Isotopo will be the upgraded
version of an existing software solution “LS-MIDA”
towards MIDA[15], proposed and developed at Prof. Dr.
Thomas Dandekar’s group of Functional genomics and
systems Biology, Department of Bioinformatics, Biocenter
at the University of Wuerzburg Germany.
The proposed prototype will be with the ability of
processing experimental isotopomer data and analysing
quantitative mass spectrometry for isotopologue mixtures of
compounds (e.g. amino acids) to derive metabolic fluxes.
The focus of software development will be towards the
prediction of relative intensities with respect to the used
mass to charge ratio values, natural abundances, relative
abundances and fractional molar abundances of each
fragment derived from the compound under study. To meet
these goals, it will implement different mathematical
algorithms including least square[16], binomial theorem[17]
matrix (inverse, transpose etc.)[18][19], mean, standard
deviation, linear[20] and multiple regression analysis[21].
The novelty which will make this application unique of
its own kind will be the processing of multi-intensity values
against one mass to charge ratio value for absolute
enrichments estimation of both natural and relative
abundances for the underlying isotopologue, with repeated
mathematical analysis for one experimental dataset.
Furthermore, proposed prototype will be able to draw the
spectrometry analysis to examine each peak of spectrum of
given mass because if it is possible to find contributions of
each molecular species, contribution from one heteroatom
(with more than one abundant isotope) can also be sorted
out[16], as the fragmentation of molecules containing
heteroatom are difficult to understand because large number
of fragments results from isotopic composition.
This manuscript mainly presents designed meta-models
for Isotopo architecture as Bioinformatical Software for
Mass Isotopomers Distribution Analysis. The overall scope
taken is deliberately broad, aiming at covering multiple
perspectives of a computational, empirical and data
management based software product development. We are
designing product line architecture[22] to make software
application flexible enough to easily adopt future updates
and additional features.
The manuscript is organized as follows: going from a
more general overview, section 2 presents Isotopo V-Model
(software development processes) and section 3 describes
Isotopo UML[23][24] designs including Use Case (Section
3.1), Data Flow (Section 3.2), System Sequence (Section
3.3), Internal Work Flow (Section 3.4), Component (Section
3.5) and Class (Section .6) Diagrams. Section 4 gives the
Software Engineering 2012, 2(4): 147-159 149
details of designed graphical user interfaces and Section 5
concludes the manuscript.
2. Isotopo: V-Model
The software development of any kind should be done
following some process model. There are already some well
established development models existing and followed e.g.
Waterfall model, Spiral model, Iterative and incremental
development, Agile development, Code and fix, and some
Process improvement models. During our software design
and development, we are following a well established
software development model i.e. V-Model; an extended
form of waterfall model proposed by Paul Rook[25].
The V-Model expresses the relationships between each
phase of the development life cycle forming typical V
shape[26] (Figure 2). The overall job of Isotopo V-Model
software development process starts with the initialization
of main concept (which in our case was MIDA), then
scientific requirements for operational scenarios have to be
clearly described and to be strictly followed to model
Isotopo. Later on following architected software designs, a
real time system has to be developed using programming,
which then has to be in house tested (integrated) and
validated by scientists. The final step is to maintain Isotopo
and if needed then repeat V-Model for software releases
with more computational and feature updates.
3. Isotopo: UML Modelling
As computational and empirical software systems
development becomes more complex, scientific academias
as well as commercial organizations require high-quality
products in short time. Unfortunately usually wrong
presumptions leads to direct software development without
adopting software development life cycle and formal design
modelling which gives a temporary and limited (scripted)
solution and in the long run it is quite difficult to enhance
and improve it. Software design modelling helps in dealing
with complexity as the meta-model architecture provides
abstraction and modification techniques which allows the
designer to concentrate on the basis of a problem by
reducing gratuitous details.
Today, a better way of architecture modelling for a newly
proposed software application is available in the form of
Unified Modelling Language (UML). It is a modelling
language, a well suited and the standard way of designing
software application by creating different abstract models.
UML is capable of facilitating software engineers stand
alone and interconnected semiformal (Meta) design views
for modelling software architectures[23].
Here software designs are created using UML principles
to have better understanding of Isotopo in terms of its
implementation, usage and working, Designed UML
diagrams describe over all feature based functionality, user
accessibility, experimental data flow, internal system work
flow, system sequence, involved component’s integration
and source code structure. In this manuscript we present
following Isotopo UML diagrams: Use Case, Data Flow,
System Sequence, Internal Work Flow, Component and
Class Diagrams. This logical design presentation will give
an overall physical view of the Isotopo focusing on its
technical architecture, grouped functionalities, flow of
information, operational perspective focusing on interface
requirements and involved technologies during software
design, development, deployment and testing.
3.1. Use Case
Use case is the specific textual and visual method of
presenting software application’s functionalities comprising
all ways of user system interactions[27]. It consists of two
main symbolic notations: Actor and Activities. In most of
the cases actor is either user or system itself as a remote
actor. Activity is the event triggered by the system in
response to the request by actor for some action.
We have designed a use case diagram (Figure 3) and
explained in detail (Table 1). The designed use case
diagram describes the user system communication for the
isotopomers experimental data analysis, which consists of a
user (actor), five direct activities (Execute LS, Input Data,
Analyze data, Visualize Results, Save results) and four
indirect activities (Open Data File, Enter data, Calculate
natural abundance, Calculate relative).
Use case diagram explains over all user system
interaction. At first user needs to execute the software
application Isotopo, then user can input experimental data
in two ways to the software application for analysis, by
entering manually and by loading experimental data file.
After data inout, user can analyse it to calculate relative
abundances. User can visualize obtained results by drawing
a mass spectrum and also can save results in the form of an
image file.
3.2. Data Flow Diagram (DFD)
Data Flow Diagram[28] presents the basic data flow
inside the Isotopo Data Analyzer (Figure 4). Data has to be
loaded from the Data File as input so called I/O Data, which
will be then analysed by the system. Systematic analysis
procedure is divided in to two levels.
First level starts by calculating relative and natural
abundances using actual intensities using user inputted
experimental. Then fractional molar abundance values and
minimum abundance values are calculated using already
calculated relative and natural abundance values.
In second level, again, new relative natural abundance
values are calculated using previously calculated relative
abundance values in level 1. Then relative abundance
values are calculated using standard intensity values,
inputted by user. Using these two newly calculated relative
and natural abundance values, likewise level 1, fractional
molar abundance and minimum values are calculated. In
third level relative difference between the observations of
level 1 and 2 is calculated.
150 Zeeshan Ahmed et al.: Formal UML Modelling of Isotopo, Bioinformatical Software
for Mass Isotopomers Distribution Analysis
Figure Legend. Software development model consisting of seven phases: Concept MIDA, Scientific Requirements, Software Design, Software
Programming, Integration Testing, System Validation and Operation and Maintenance.
Figure 2. Isotopo; V-Model Software Development Process
Figure Legend. Use case diagram of Isotopo is consisting of a User, five direct and four remote (indirect) activities.
Figure 3. Isotopo; Use Case
Software Engineering 2012, 2(4): 147-159 151
Table 1. Isotopo; Use Case
No.
Isotopo
Features Descriptions
1 Number 1
2 Name Isotopo Data Analyzer
3 Application Isotopo
4
Description
This use case consists of a User, five direct
and four remote (indirect) activities. This
describes the user (actor) system (Isotopo)
communication for the isotopomers
experimental data analysis.
5 Primary Actor User (1 Actor)
6 Precondition
Software application successfully running.
7 Trigger /
Events
• Execute LS
• Input Data
• Open Data File
• Enter data
• Analyse data
• Calculate natural abundance
• Calculate relative
• Visualize Results
• Save results
8 Basic Flow
Basic flow consists of following steps:
1. Start software application
2. Enter input data by either loading from
data file or by manually entering.
3. Analyse input data.
4. Visualize results
5. Observe predicted results (text and image).
6. Save obtained results for reuse.
9 Alternate
Flows Exception will be notified to the user.
3.4. System Sequence Diagram (SSD)
The System Sequence Diagram represents a particular
scenario (text or graphic) defined by use case, especially for
transaction oriented systems[29]. A SSD consists of actors
(users), messages (methods) called by the actors, return
values (optional, if any) and loop indicators. The main
reason of using SSD is to explore the logic of multifaceted
operations (procedures or functions).
The system sequence of Isotopo Analyzer is consists of
seven sequential steps with individual tasks (Figure 5). At
first the experimental data (Metabolite, Actual Mass to
charge ratio (M/Z) Values, Actual Relative Intensity (RI)
Values, Standard M/Z Values, Standard RI Values and
Number of Fragments) has to be inputted to the system via
the user via graphical user interface.
Figure Legend. The data flow diagram of Isotopo is consisting of a File
(Data File), one main Function (Analyze I/O Data) and eight internal
functions: Calculate Natural Abundance Values and Calculate Relative
Abundance Values, Calculate Fractional Molar Abundance, Calculate
Minimum Abundance Values, Calculate Relative Natural Abundances
using previously calculated Relative Abundances, Calculate relative
difference between the observations of Level 1 and Level 2, Calculate new
Minimum Abundance, Calculate new Fractional Molar Abundance and
Calculate Relative Abundances using standard intensities
Figure 4. Isotopo; Data Flow Diagram
152 Zeeshan Ahmed et al.: Formal UML Modelling of Isotopo, Bioinformatical Software
for Mass Isotopomers Distribution Analysis
Figure Legend. The abstract system sequence diagram of Isotopo is consisting of seven steps (Isotopo, Analyzer, Relative Natural Abundances, Relative
Abundance Values, Abundance Matrix, Fractional Abundances and Minimum Abundance values) with several directing arrows in between.
Figure 5. UML System Sequence Diagram (SSD)
System at first analyses inputted data by validating it.
After successful validation data will be sent to Isotopo
Analyzer to calculate abundance values. Isotopo Analyzer
then sends information based on number of fragments to the
Relative Natural Abundances, which calculates relative
natural abundances (n) and sends to Isotopo Analyzer.
Then, to calculate relative abundance values, Isotopo
Analyzer sends calculated natural abundance values and
actual Ri values to the step 4 i.e. Relative Abundance
Values Ccalculator, which creates abundance matrix of
calculated natural abundance values (Mn) using step 5 of
system sequence i.e. Abundance Martix. Later after
performing mathematical operations, sends back the
resultant relative abundance values (RMn) to the Isotopo
Analyzer.
Then, to calculate Fractional Molar Abundance values,
Isotopo Analyzer sends natural abundance matrix values
and calculated relative abundance values to the step 6 i.e.
Fractional Abundances, which later after the mathematical
operation performance sends back resultant fractional molar
abundance values (FRMn) to the Isotopo Analyzer.
Later after, to calculate minimum abundance values,
Isotopo Analyzer sends calculated fractional molar
abundance values, standard relative intensity values to step
7 i.e., Minimum Abundance Values, which then later after
the calculation of minimum values send back resultant
values (Min Val) to the Isotopo Analyzer. This was the
first complete transaction of different abundance value
calculations.
3.3. Internal Work Flow Diagram
Internal flow chart is also known as the Flow chart; a step
by step visual representation of defined interlinked
processes (operations) in a software application[30],
categorized in different shaped boxes representing different
kinds of operations connected by directional and
unidirectional (associated) arrows.
As the whole software application is divided in to two
main modules: Data Analyzer and Data Manager. The
internal work flow of Isotopo Data Analyzer (Figure6)
starts with experimental data input from data file which
then formatted by the system and resultant structured data
Software Engineering 2012, 2(4): 147-159 153
will be displayed in graphical user interface of Isotopo Data
Analyzer.
Later selected data by the user from graphical user
interface is taken by the system to calculate natural, relative,
fractional molar abundances and minimum values with the
ratio of two. Then differences between to transitional
abundance values is calculated and based on the resultant
information a spectrum will be drawn by the system, which
will be presented in graphical form at graphical user
interface for the user visualization and analysis.
The internal work flow of the Isotopo data manager starts
with experimental data manipulation (Figure 7), which
leads to the experimental data extraction from existing data
files and storing data by creating new data files.
Furthermore it displays data loaded from data file into
system and let user manipulate it by adding some new data,
merging data from other files, deleting some data, and
updating data.
3.5. Component Diagram
Component diagram is the visual presentation of
assembled constituents representing structural relationship
between service provider and consumer[24].
Figure Legend. . The flow chart of Isotopo Data Analyzer is consisting of one starting point (Start), one Input point (Experimental Data; Data Files), one
formatting point (Format Data; Display in lists), one data selection point (Select Data to Process), processing units (Calculate Natural Abundance Values,
Relative Abundance Values, Fractional Molar Abundance, Minimum Abundance Values, Average Differences and Standard Deviation), one visualization
mode (Draw Spectrum) and one ending point (End).
Figure 6. Isotopo; UML Flow chart of Data Analyzer
154 Zeeshan Ahmed et al.: Formal UML Modelling of Isotopo, Bioinformatical Software
for Mass Isotopomers Distribution Analysis
Figure Legend. The flow chart of Isotopo Data Manager is consisting of one starting point (Start), one Input point (Experimental Data; Data Files), one
formatting point (Format Data; Display in lists), one data file creation process, one visualization mode and one ending point (End).
Figure 7. Isotopo; UML Flow chart of Data Manager
It allows the designer to confirm system's functionality to
be implemented in the form of components using internal
and third party services (e.g. programming languages,
libraries, executables, application programming interfaces,
frameworks etc.) in terms of nature and behaviour.
Isotopo is mainly consists of two modules i.e. Isotopo
Data Analyzer and Isotopo Data Manager (Figure 8). User
can access these both modules to perform mass isotopomers
distribution estimation and file based experimental data
management. Isotopo, as whole application, is developed
using an object oriented platform independent language C
Sharp (C#) and Microsoft Dot Net technology.
Figure Legend. The component diagram of Isotopo is consisting of one
platform component (Microsoft Dot Net), one main component (LS), two
subcomponents (Analyzer and Data Manager).
Figure 8. Isotopo; UML Component Diagram
3.6. Class Diagram
Class diagram is the static representation of relationships
between defined classes for the development of a software
application[31],[32]. The source code of Isotopo will be
divided into three namespaces i.e. SBEDA, System and
ZEDGraph. SBEDA is the main namespace containing all
related and newly developed source code classes, System is
the by default namespace provided by C-Sharp language
used during the software development, and this namespace
is responsible for providing access to default language
based controls and components. Namespace REDGraph is a
third party application programming interface used mainly
for the development of graphical visualization of statistical,
mathematical and experimental data in the form of two and
three dimensional colored bar charts.
There are seven newly developed interlinked classes:
Main, IsotopoDataAnalyzer, Isotopo DataManager, Isotopo
About, Calculation, Complex and Matrix (Figure 9). As
Isotopo is a multi document interface (MDI) application,
Main MDI parent class which contains all other child
classes. IsotopoDataAnalyzer is the multi attribute class
developed as the graphical user interface of the Isotopo
analyzer which provides all visual options to the user to
load, edit, analyze and visualize experimental data and
observed results.
IsotopoDataManager is the multi attribute class
developed as the graphical user interface of the Isotopo
Data Manager which provides all visual options to the user
for file based experimental data management and
manipulation including entering, loading, editing, updating,
deleting, merging, replacing and saving data in files.
Calculations is the multi attribute class developed for
performing all mathematical operations including mass
value estimations, relative abundances, data parsing and
different data format conversions.
Matrix is the multi attribute class developed for
performing matrix operations including drawing simple
matrix of NxM rows and columns, calculation inverse and
transpose of matrix. Complex is the multi attribute class
developed for difficult mathematical operations including
square root, absolute, tangent and operator overloading.
IsotopoAbout is the single attribute class, providing
information Isotopo and development team and research
group.
Main sequence of classes, starts with Main container
class, which provides other graphical user interface based
classes IsotopoDataAnalyzer, IsotopoDataManager and
IsotopoDataAbout. IsotopoDataAnalyzer perform user
system communication, let user enter, edit and visualize
experimental data, and analyze experimental data by
directly using class Calculations which the uses classes i.e.
Matrix and Complex. IsotopoDataManager is an
independent multi attribute class performing operations
including user system communication for file based data
management and manipulations.
LeastSquareDataManager is the multi attribute class
developed as the graphical user interface of the Isotopo
Software Engineering 2012, 2(4): 147-159 155
Data Manager which provides all visual options to the user
for file based experimental data management and
manipulation including entering, loading, editing, updating,
deleting, merging, replacing and saving data in files.
Calculation is the multi attribute class developed for
performing all mathematical operations including mass
value estimations, relative abundances, data parsing and
different data format conversions.
Figure Legend. The class diagram of Isotopo consisting of three name spaces (SBEDA, System and ZEDGraph), one main class (Main), six multi
attribute classes (IsotopoDataAnalyzer, IsotopoDataManager, IsotopoAbout, Calculation, Complex and Matrix) and one single attribute class
(IsotopoAbout).
Figure 9. Isotopo; UML Class Diagram
156 Zeeshan Ahmed et al.: Formal UML Modelling of Isotopo, Bioinformatical Software
for Mass Isotopomers Distribution Analysis
Figure 10 (a). Designed Main Graphical User Interface
Matrix is the multi attribute class developed for
performing matrix operations including drawing simple
matrix of NxM rows and columns, calculation inverse and
transpose of matrix. Complex is the multi attribute class
developed for difficult mathematical operations including
square root, absolute, tangent and operator overloading.
LeastSquareAbout is the single attribute class, providing
information on Isotopo and development team and research
group.
4. GUI Design
This section intends to provide an overview of Graphical
User Interface (GUI) designing and basic understanding of
the proposed Isotopo GUI. Targeting the challenge of the
proposition of designing a standardized graphical user
interface, a review research is conducted in a chosen the
field i.e. Human Computer Interaction (HCI), to have
complete understanding of graphical user interface design
and development. HCI is renowned as Human Machine
Interface (HMI); the study of designing, evaluating and
implementing interactive computing systems for human
use[33]. Designing High quality HCI design is difficult to
implement because of many reasons: market pressure of
less time development, rapid functionality addition during
development, excessive several iterations, competitive
general purpose software and human behaviour analysis.
Designing human computer interaction interface is an
important and a complex task, but it could be simplified by
decomposing task into subcomponents and maintaining
relationships among those subcomponents. Task
decomposition is a structured approach, applicable in both
Software Engineering and Human Computer Interaction
(HCI) fields depending on specific processes and design
artifacts. Using design artifacts applications could be made
for analysis and design by making the hand draw sketches
to provide high level of logical design based on user
requirements, usage scenarios and essential use cases. To
design hand drawn sketches there are some strategies to be
followed .i.e., planning, sequential work flow, and levels of
details. While evaluating or designing a user interface, it is
important to keep in mind the HCI design principles. There
are four major HCI design principles .i.e., Cooperation,
Experimentation, Contextualization, Iteration and Empirical
Measurement[33].
Software Engineering 2012, 2(4): 147-159 157
Like software engineering design patterns there are some
graphical user interface design patterns (Window Per Task,
Direct Manipulation, Conversational Text, Selection, Form,
Limited Selection Size, Ephemeral Feedback, Disabled
Irrelevant Things, Supplementary Window and
Step-by-Step Instructions) needs to be strictly followed in
software graphical user interface design. These patterns
help designers in analysing already designed graphical
interfaces and designing a user friendly and required on
demand graphical interface.
As the proposed software will probably be used by the
scientist belonging to the fields of Biology and related
fields (e.g. Biochemistry etc.), the major need of the design
is to be simple and easy to use, as most of the time people
belonging to aforementioned fields are not interested in
learning and spending time familiarizing their selves to new
software application.
The designed graphical user interface[34] of Isotopo Data
Analyzer is presented in Figure 10 and Data Manager in
Figure 11. The graphical user interface of Isotopo data
analyzer consists of 10 main controls: open data file, clear
all text controls, measure selected data, process all data,
remove selected data, open data manager, close Isotopo,
selected values and results.
Moreover the graphical interface is divided into seven
views: Isotopo Analyzer, Fragment Viewer, Spectrum
Viewer, Result Viewer, Relative Abundance 1, Relative
Abundance 2 and Relative Abundance 3.
The graphical user interface of Isotopo Data Manager
consists of 16 main controls: open data file, clear all text
controls, close isotopo data manager, add new values,
update edited values, clear text fields, save data in file,
select values to edit, delete values, create new data file,
select source directory, save file, cancel creating file, data
view, Open Isotopo Data Analyzer and Open Isotopo Data
Viewer.
Figure Legend. The Isotopo GUI of Data Analyzer (a) presents the main graphical user interface responsible for handling user data input, analyzing and
producing spectrum, along with (b): Isotopo; Fragment Viewer, (c): Isotopo; Spectrum Viewer, (d): Isotopo; Result Viewer, (e): Isotopo; Relative
Abundance 1, (r): Isotopo; Relative Abundance 2, (g): Isotopo; Relative Abundance 3.
Figure 10. Isotopo; Designed Main and Analyzer Graphical User Interface
158 Zeeshan Ahmed et al.: Formal UML Modelling of Isotopo, Bioinformatical Software
for Mass Isotopomers Distribution Analysis
Figure Legend. The Isotopo GUI of Data Manager presents the main graphical user interface responsible for handling user data input and providing data
management and manipulation options.
Figure 11. Isotopo; Designed Data Manager Graphical User Interface
5. Conclusions
In this manuscript we have presented newly proposed and
formally modelled bioinformatical software for mass
isotopomers distribution analysis.
This manuscript thus provides guidance in advance for
using the release of the architected meta-models and
designed user interface of Isotopo
Now we are looking forward to successfully implement
designs using V-Model software development model.
ACKNOWLEDGEMENTS
We (authors) are thankful to the Department of
Bioinformatics, Biocenter, University of Wuerzburg
Germany for giving us the opportunity to work on this
research.
We are thankful to the editor for considering, blind
reviewers for reviewing and publishers for publishing this
manuscript.
We thank German Research Foundation (DFG)[TR34-Z1]
for funding this research.
Author’s Contribution
Zeeshan Ahmed architected software designs and drafted
manuscript as the First and Corresponding Author. Saman
Majeed contributed in writing of the manuscript as
co-author. Prof. Thomas Dandekar Lead and guided the
study.
All authors participated in evaluation of the architecture
designs as well as writing of the manuscript.
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