APIC : A Generic Interface for Sequencing Projects

Gflles BISSON, Alain GARREAU

CNRS (IMAG-LIFIA), INRIA RhSne-Alpes46 avenue Ftlix Viallet, batiment Hitella

38031 Grenoble Ctdex 1, Franceemall : gilles.bisson@imag.fr

Abstract

In this paper, we describe the APIC graphical interfacethat aims at displaying the results produced by thegenornic sequence analysis methods and at helping acomparison of these results. The major feature of APIClies in its genericity. As a matter of fact, this interfacecan obviously be used to visualise genetic or physicalmaps but it also able to display other kinds ofinformation such as curves or pictures. On the one hand,APIC provides the biologist who builds a new sequenceanalysis method with a standard interface allowing todisplay his results. Thus, he can avoid implementing aspecific visualisation tool. On the other hand, evenwhen the methods already have their own interfaces,using APIC has the advantage of giving a homogeneousway to compare several results coming from differentanalysis tools. Moreover, it provides some powerfulfunctions for navigating and browsing into the results.

1 MotivationsTo handle the large amount of data and knowledge

produced by the sequencing projects, the approaches usinga standard data base schema can no longer be used. As amatter of fact, as shown by (Durbin, Mieg 93) themanagement of these data and knowledge involves somespecific problems that do not come down to a simpleproblem of information storage. On the one hand, theelaboration of new knowledge through the sequencingproject involves a fast modification of the biologicalparadigms. Thus, one needs to be able to modifyincrementally the modelling schema used in theknowledge bases. On the other hand, the info~’anationcontained into the knowledge bases bring the ground facthelping the research of new knowledge. Thus, we need tosupply some suitable and efficient interface to thebiologist to access to the content of these knowledgebases. The system ACeDB (Durbin, Mieg 92), which hasbeen initially implemented in the frame of the project forobtaining the genomic sequence of the nematodeC. Elegans, is one of the most popular knowledge basemanagement system currently used by the sequencingprojects. Its success is partially due to its powerfulgraphical interface allowing the biologists to visualisethe data in the form of a biological map (genetic,physical .... ) and to navigate from map to map.

In the frame of a project (Mtdigue et aL, 95) supportedby the GREG1 we are developing the generic mappinginterface APIC2. Here, the word generic have threedifferent meanings. Firstly, this interface is not dedicatedto a specific organism. Secondly, this interface is able todisplay in a homogeneous way many kinds of genomicmaps (cytogenetic, genetic, physical .... ). Finally, APICis not limited to the display of biological entities but isalso able to display the graphical objects (curves orpictures) produced by the sequence analysis methods.

Before detailing more precisely the functionalities ofAPIC and its specificities with respect to the otherexisting products such as ACeDB (Durbin, Mieg 93),SIGMA (Cinkosky, Fickett 92) or GnomeView (Douthartet al. 94), it is necessary to express the context in whichthis product has been implemented. Currently, the studyof a genomic sequence of an organism involves twodifferent requirements. On the one hand, one needs tomanage a set of biological and bibliographical informationabout this genome. On the other hand, one needs toimplement some specific analysis methods to deal withthis genome (for instance, the search of coding parts, ofhomologies .... ). Therefore, two kinds of knowledge mustbe handled in the course of a sequencing project :

¯ descriptive knowledge that axe used to &fine thebiological entities of the genome, to describe therelationship between these entities and finally to indicatethe related bibliographical references.

¯ methodological knowledge that axe made of twoparts. Firstly, a set of general purpose sequence analysismethods, such as BlastX (Altschul et al., 90), whosealgorithms are rather independent of the genome understudy. Secondly, a set of analysis strategies more relatedto the genome under study. Each analysis aims at dealingwith a particular task, each task being solved by calling a

I From french acronym: "Groupement de Recherches etd’Etudes sur les G6nomes". This project have four partners:Curie Institute in Paris, Laboratory of Biometry, Genetic etBiology of Populations in Lyon, L’INRIA Rh6ne-Alpes inGrenoble and the ILOG company in Paris.

2 From french acronym "Aide a la Pr~entation desInterf ~aces Cartographiques"

Bisson 57

From: ISMB-95 Proceedings. Copyright © 1995, AAAI (www.aaai.org). All rights reserved.

sequence of general purpose methods with some specificparameters. For instance, the biologist can look for thecoding part of a sequence by successively runningBLASTX, searching for the ORF (Open Reading Frames),and searching for the CDS (CoDing Sequences). It worth noting that the structure of an analysis strategy canbe very complex and involves several iterations, tests andcalls for other more elementary strategies.

Until now, the sequencing project managers havemainly focused on the problem of modelling thedescriptive knowledge. Obviously, it is generally possibleto introduce in these systems some new methods toanalyse the genome, unfortunately these additionsinvolved the use of programming tools. Our project aimsat providing the biologists with a cooperative workbenchallowing (1) to manage both descriptive andmethodological knowledge (2) to reuse as far as possiblethe existing analysis methods (3) to implement newstrategies without programming. The descriptiveknowledge is managed with the object-oriented modellingtool TROPESa (Mariflo et al. 90) and the methodologicalknowledge is managed with SCARP (Willamowski 94 Mddigue et al. 93) that allows a declarative definition ofthe solving strategies. The final system will focus bothon ergonomy and extendibility.

¯ Ergonomy. Thanks to the explicit definition of thesolving strategies, the system can give some advices tothe biologist about the general method to use for solvinga given analysis task, or it can indicate the right strategiesto apply for solving a complex analysis task. In thisframework, the graphical interface APIC allows tocompare easily the results produced by the differentanalysis methods and provides some powerful functionsfor navigating and browsing into these results.

¯ Extendibility. Obviously, the final system will beable to store and manage the sequences produced by thesequencing tasks and the new data and knowledge createdby the analysis of these sequences. However, neither theset of the biological entities defined in the system nor theanalysis methods and strategies used to deal with theseentities are fixed. It is always possible to add new analysisstrategies or to improve the existing ones. Similarly, thesystem can be adapted to some specific applicationcontexts by adjoining new sequence analysis methods.

As previously said, one of the major features of asequencing project manager is its ability to display theinformation known about the genome in a comprehensiveform and to supply some high level tools for browsingand navigating in the knowledge base. In our project, as itis possible to introduce new analysis techniques, weabsolutely need to provide the biologist with a generictool allowing to visuaiise and compare the resultsgenerated by these new methods (figure 1). As a matter

3 In the final release of the project. Currently we use themodelisation tool Shirka (Rechenmann, Uvietta 91).

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fact, it is worth noting that these methods have notalways a built-in display interface, especially when theyare totally new. The advantages of using such a genericapproach are threefold. First, APIC brings a standardinterface displaying the information in an homogeneousway, therefore, the comparison of the results is makeeasier. Moreover, the user’s task is simplified since be hasto manipulate only one general interface instead of a set ofdedicated interfaces. Finally, by separating thevisualisation interface from the sequence analysismethods, one obtains a more modular system whosefurther evolution will be made easier.

Figure 1 : a genetic tool for displaying and comparing theresults produced by the analysis methods

In this paper, we are going to present the generalfunctionalities of APIC and the underlying concepts used(section 2). Next, in the sections from 3 to 7 we willdetail the main features of the system such as zooming,synchronised scrolling, surimposing of curves andcustomisation of the interface. Finally, we will providesome information about the implementation (section 8).

2 A generic approach

2.1 IntroductionThe different sequence analysis methods produce a great

diversity of results such as new entities, sequence,genomic map, curves, drawings ... whose biologicalmeaning are different. Therefore, to specify the features ofour generic interface we are temporarily going to forgetthe biological aspects and we are going to analyse thisproblem from a strictly graphical standpoint (figure 2).

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Figure 2 : a graphical point of view of the interface

Practically, in most of the situations the problemcomes down to representing a set of graphical objects onan oriented and graduated axis (horizontal or vertical).These graphical objects eaa be points, segments, curves orpictures and can be seen as the display of a set of boxes

containing various patterns. Finally, several annotationscan be linked to these graphical objects such as theirname, their sequence of nucleotides or thek orientation inthe axis. In conclusion, we see that an interface comesdown to a small amount of graphical concepts.

However, an interface is not restricted to the display ofa graphical representation. It must also provide severalmanipulation functions allowing the user to browse and tonavigate into these representations. Again, the set ofuseful functions is relatively small and can be definedindependently of the biological problem. Here are a list ofsome of the relevant functions :

¯ Displaying simultaneously several kinds of mapsshowing different set of information.

¯ Easy and quick selection of the types of objects wewant to display in the maps.

¯ Possibility of accessing (read/write) to the informationcontained in the KB through the interface.

¯ Zooming (in and out) into the maps until thesequences of nucleotides become visible.

¯ Providing multiple methods to navigate in the mapsand to memorize the relevant sites.

¯ To be able to synchronised the scrolling between mapshaving different scales and different units.

¯ Possibilities of surimposing different kinds ofinformation on the same display.

¯ Customisation of the interface by the user (choice ofthe colors, settings of the layout, ...).

2.2 Basic notions

In the interface APIC, a map is an oriented andgraduated window containing a set of graphical objects.Each map is described by its name and its unit 4 (Kb,CentiMorgan .... ), however the list of these units is notfixed and the user can easily define a new unit. Eachgraphical object is typed and have a beginning and endingpositions in the sequence, both positions are expressed inthe unit of the corresponding map (figure 3). The notionof type is very important since the display settings areperformed according to the type of the objects. In otherwords, all the objects belonging to a given type will bedisplayed in the same way in a map. Several optionalattributes can be associated to an object such as its name,its shape (plain pattern, curve or picture), its uncertaintyconcerning its position in the sequence, its orientationinto the map (3’ or 5’) and the sequence of nucleotides.Finally, other attributes can be freely provided to theinterface, for instance to express some biological data.These last attributes are not directly used by the interfacebut can be viewed by the user by clicking on the object.

In the current implementation of APIC, the descriptionof a map is given to the interface in the form of a readonly text file using the format TINA. This formatconsists of a non-ordered sequence of records. Each records

4 Some other attributes exist such as the accurraey or theorigin of the map. There will not be detailed here.

describes one entity of the map whose features aresummerized by a non-ordered set of attributes (figure 3).

Sequence Bsor~cds 57~ Shape

Name o"’~ "~""" Orientation

Type {CDS}Name {Bsoric.cds 57}Frame (2}Begin {i00)End {121}Sequence {ATGCGATTGAAGTCGATGAAA)

Figure 3 : graphieai representation of an object in a mapand its description in the TINA format

Thanks to this general definition of the notion ofobject, the system can easily take into account somespecific graphical data such as curves or pictures sincethey just consist in objects filled with particular patterns.

However, a problem remains : all these objects eannotbe placed anywhere within the map and we can statedseveral requirements. Generally, it is necessary to avoidany kind of overlapping between the objects. However,when the interface displays an object such as a curve, itcan be very interesting to surimpose this curve above (orunder) the other entities of the map. In other respect, weneed to be able to group the related biological entities intothe same area of the map. For instance, if there are someobjects on the map standing for the codons STOP of thesix reading frames of a sequence, it is relevant to organizethese codons frame by frame in the map.

M’ddl~ ~d~acr.Sro~md ~ r.ore~d

~ Layer 3

F’mal display Layer 2

Figure 4 : in APIC a map is structured following thenotions of layers and levels

Thus, in order to fulfil all these requirements, we haveintroduced in APIC the notion of layers and the notion oflevel (figure 4). Layers are a horizontal structuration of themap, each map can contain up to ten different layers. Ineach layer the user can put one or several types of objects.

Bisson 59

Figure 5 : general aspect of the interface

For instance, in the case of the codons STOP, the usercould assign each frame to a specific layer : in this way,the 6 frames are displayed into 6 raws as in the interface ofRECSTA (Fichant et al. 87). The height of a layer isdynamically computed by APIC according to the objectshold in this layer. This notion of layer is roughlyequivalent to the notion of "tiers" used by SIGMA.

The notion of level is more original. In practice, eachlayer of APIC can have three different levels of display :foreground, middle ground, background. The types ofobjects that are placed in the middle ground level areautomatically shifted on the Y-axis so that there is nooverlapping between the different objects belonging tothis level. In other respect, the types of objects that areplaced into the two other levels are displayed withouttaking care of the overlapping problem. In that case, theuser can provide, in the description of an object, theabsolute Y-position (in pixels) of this object in the level.

The final display is performed by merging the threelevels (figure 4). Thanks to this mechanism, the user canstructure the maps and he can create rather complexdisplays (section 6). For instance, he can easily surimposesome cytogenetic bands, a list of genes and a set of curveson the same screen. Finally, it is worth noting that thestructuration of a map is performed by the user after theloading of this map in the interface and by interactingthrough a set of dialogue boxes. Therefore, there is a clearseparation between the biological knowledge which isdescribed in the TINA file and the representational choicesdone in the interface. Obviously, all these choices can be

saved in a resource files and reused on some other mapscontaining the same types of objects.

3 General aspect of APIC

The APIC interface consists in a X11 window (figure5) in which one or several maps can be simultaneouslyloaded. The maps loaded by the user can express differentkinds of knowledge (physical, genetic .... ). Each map topped (1) by a scale whose graduations are expressed the units of the map and (2) by an optional commandpanel providing some basic functions allowing to navigateinto the map (zoom, scrolling .... ). These functionalitiesare described in section 5. Finally, the user can change theorder of the maps and can hide the command panel.

In the example figure 5, the three maps visualise theresults found by three sequence analysis methods for allthe reading frames of a sequence. Top-down, we find themap of the homologies found by a BlastX into a proteindatabase, the entities found by an ORF research (OpenReading Frames) and the entities found by an RBS/CDSresearch (Ribosome Binding Site/CoDing Sequence). the third map, the RBS and CDS has been splitted by theuser into two different layers. This structuration intolayers increases the readability of the map. The possibilityof loading several maps in the interface makes easier forthe biologist the comparison of the content of these maps.For instance, we can see that there is a close similaritybetween the structure of the ORF and the CDS (secondand third maps) in the right part of the window.

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APIC - Alde.a la.Prese~ des Interfaces Cm’tognq)hlgues ii

Figure 7 : synchronised scrolling between a genetic and a physical map

4 Scrolling and navigationThe quality of a mapping interface strongly depends on

the quality of the navigation functions provided to the usersuch as the scrolling and the zooming. In practice, whenwe work on a set of related maps in a window, it isinteresting to group these maps together such that theyhave the same behavior with respect to the navigationfunctions. For instance, in figure 5 when we move thescroll bar of the first map, it would be nice to moveautomatically the scroll bar of the second map from adistance corresponding to the scales ratio between thesemaps. This possibility has been implemented in APICthrough the notion of hook. When two or several mapshave been hooked in the interface, all scrolling orzooming actions performed on one map of the hook areautomatically applied to the other maps of this hook.

Map 1

Map 2

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:::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::

Figure 6 : computation of the scale factors between theshared objects of two maps

Obviously, this function is easy to implement whenall the maps use some similar scales, the interface justneed to have the conversion table between the different

units. However, the situation can be also more complex:for instance in figure 7 we have loaded a genetic mapwhose scale is expressed in minutes and a physical mapwhose scale is expressed in Kilobases. Here, the twoscales are not linearly correlated, moreover the objects donot always occur in the same order in the two maps.Therefore, to synchronise the scrolling between these twomaps, APIC uses a special algorithm based on the notionof shared objects (figure 6) ; the idea is the following.When several maps {M1 ..... Mn] have been hooked

together, for each pair of map Mi and Mj, the systembuilds a table in which each cell corresponds to theinterval between two consecutive anchorage points. Ananchorage point corresponds either to the beginning of ashared object~ or the end of a shared object.

Next, each cell of this table is set to the scale ratiobetween the segment in Mi and the segment in Mj. Anegative scale ratio is generated when there is an inversionbetween the positions of two objects in the sequences andthus the two maps will be moved in an opposite wayduring the synchronised scrolling. Here is the tablegenerated for the example in figure 6 :

Map origin Begin object 1 SR 1

._.B.._e_.~n_object 1 End object 1 SR 2

End objec, t 1 Begin object 2 SR_~..Be~, object 2 End object 2 SR 4End object 2 - ,, ,Ma,~ end SR 5

Two objects are considered as being identical is theyhave the same type and name in the two maps.

Bisson 61

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Figure 8 : the command panel of APIC

Thanks to the previous table, it becomes possible tosynchronise the scrolling of the maps. In this way, infigure 7, when the user moves the scroll bar of thephysical map, the genetic map is scrolled too and whenthe cursor (which corresponds to the vertical line) pointsat a common object in the physical map (here HtpG) always points at the same object in the genetic map.

Concerning the navigation in the sequence, ourinterface provides a large set of functions to the biologist.These functions can be used through the command panelplaced above the map (figure 8).

¯ The left part of the command panel indicates thecurrent position in the sequence. This current position ismaterialised in the map through the medium of a smalltriangle placed in the scale. The user can change thisposition by introducing by hand a new value in the fieldposition. When a new position is given the current map isscrolled and the hooked maps are scrolled too.

¯ The second part of the panel allows the user to shiftthe genomic map from left or right. There are twodifferent kinds of moves. On the one hand, the user canspecify a type of object and move the map from object toobject. For instance, by clicking on the upper right button(next), the user will move the map toward the next gene the right of the current position. On the other hand, the

map can be scrolled following a given step that the usercan edit. In figure 8, this step equals lminute in thegenetic map and 1 Kb in the physical map.

¯ The third part of the panel controls the zoomfunctionalities. The user can increase or decrease the scaleof the map by clicking on the button Zoom-Out or Zoom-In. During a zoom, the user can decide if a zoom concernsthe current map only or all the maps that have beenhooked to this map. The increase/decrease factor of thescale is defined in the field "factor" that can be edited. Thebutton ALL allows to select a scale factor allowing to seeall the current genomic map, and the button CENTERallows to center the map on a given position.

¯ The fourth part of the panel concerns the cursor.This cursor allows to visualize the current position in themap in the form of a thin vertical line and it can be shownor hidden. The user can also put a mark into the currentmap ; once the mark is set the field "dist" visualises thedistance between this mark and the current position of thecursor. In this way, the biologist can easily measure thedistance between any two objects of the map.

¯ Finally, the right part of the interface allows the userto memorise some "views" of the current map. Themechanism is closely related to the one used in thehandheld computers. When the user stores a view m the

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:~ ~..,..i:i:i:i..2i::. "::.’:’~.................... .:::, .....................................Figure 9 : display settings for the different types of objects

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memory number M, the interface memorises the positionand the scale factor of the current map. When the contentof the memory M is recalled, the interface restores theposition and the scale previously memorised. In this waythe user can easily toggle between different parts of themap without doing any scrolling. When the content of amemory is recalled all the maps that have been hooked tothe current one are automatically scrolled.

5 Information to displayAccording to the problem under study, the

visualisation of the all the information associated to theobjects such as their names or their orientations in thesequence, are not always relevant.

APIC allows the user to set the display for each typeof objects through a dialogue box (figure 9). The spread a display setting can concern either the current map, allthe maps hooked to the current one or all the maps of theinterface. For instance in figure 9 we only display thenames of the CDS belonging to the frame 1. In otherrespect, the user can temporarily show or hide a giventype of object through the buttons occurring in the field"filter". Finally, with the field "object as" the user canchoose if an object is always displayed as a point(independently of the scale) or as a scaled segment.

6 Curves and sequencesAs emphasized in the section 2, the visualisation of

the results produced by the sequence analysis methods arenot always restricted to the display of a set of objects.Figure 10 shows an example of a more complex display.This figure displays the results of a contig analysis onthree reading frames. The arrows stand for the CDS, the

rectangles stand for the homologies found by BlastX andthe curves have been produced with GenMark(Borodovsky, Mclninch 93) to predict the coding parts the sequen~ from a statistical analysis of the codons. Asshown in the bottom part of this figure the user can easilydisplay the information associated to an object by clickingon it. Here, the selected object is "ak2 bacsu" whichoccurs in the second reading frame.

To obtain this screen, the biologist has performed twooperations. First, he has translated the output of theanalysis methods into a text file (in the TINA format)containing the list and the description of the objects todisplay and the coordinates of the points of the curves.Second, he has loaded this file in the interface andassigned the different types of objects to three differentlayers (one for each reading frame) ; next he has put theCDS and the homologies into the middle ground level andthe curves into the foreground level. Therefore, once thetranslation procedures between the output of the sequenceanalysis methods into the TINA format are written, thedisplay of these results can be automatically achievedwithout any programming.

The map in figure 11 shows how our interface displaysthe sequences of nucleotides. In APIC, the sequence ofnucleotides associated to an object becomes automaticallyvisible as soon as the scale factor is sufficient. However,from a practical point of view the letters ATGC whichcompose a sequence become easily readable only when thesize of the font is greater than 8 points. Therefore on ascreen having 1000 points it is only possible to display asequence up to 120 nucleotides. To overcome thisproblem APIC proposes another representation mode inwhich the nucleotides are represented as colored strips. Inthis way, the interface can display larger sequences sincethe minimal size for a nucleotide is now 1 pixel. This

Figure 10 : curves and other biological entities

Bisson 63

Figure 11 : APIC proposes different modes to display the sequence of nucleotides

new representation is also interesting because it is well-adapted to the research of regularities into a sequence.

7 Customisation of the interfaceAs shown in section 5, APIC allows the user to select

the information to display in the maps. But it is alsopossible to change the overall aspect of the entities thanksto the dialogue box shown in figure 12. In this way, thebiologist can modify the representation associated to eachtype of objects according to the kind of knowledge hewants to bring to the fore.

For instance, in the field "object" of this dialogue box,the biologist can modify the shape, the color, the size andthe layout (offset and height) of the different types object. As in the display settings (section 5) themodifications performed on a type of object can concerneither a map, all the maps hooked to the current map or

all the maps of the interface. In the field "sequence", theuser can modify the color associated to each nucleotide inthe colored strip mode and the minimal size of font to useto display the letters of the sequence. It is worth notingthat all these settings can be saved and reused on anothermap containing the same types of objects.

8 ConclusionIn this paper we have presented the main characteristics

of APIC, a generic interface allowing to visualisegenomic information. Genericity is the main strength ofthis interface since it allows the system to deal with alarge panel of information without involving anyprogramming from the user standpoint. Clearly, the majordifference between APIC and the other existing interfaceslies in the fact that APIC is just a visualisation interfaceand not a database manager, nor a sequence analysis tool.

Figure 12 : customisation of the interface by the user

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However, in the project supported by the GREG all thesefeatures exist but there are managed at the level of theobject-oriented modelling tool TROPES and the level ofthe sequence analysis manager SCARP. Thanks to thismodular architecture, the system has the advantage toprovide an homogeneous interface allowing to displaymany kinds of information (biological and graphical) in structured way through the notions of layer and level.Furthermore, the navigation facilities (synchronisedscrolling .... ) provided by APIC and its ability to structurethe display makes the comparison of the results producedby the sequence analysis methods easier.

iiiiiiiiii iiiiiii!i %iiiiiiiiiiiiiiiiiiiiiii iii iiiiiiiii~ ~ ............ !iiiiiiiiiiiiii .....

Figure 13 : the different implementations of APIC

From a technical standpoint, APIC has been developedin C++ with the help of the interface builder ILOG-VIEWS (Ilog 94). In the current version of APIC, thecommunication between the sequence analysis managerand the interface is done through a read only text file inthe TINA format. In the next release the communicationwill be directly ensured through a set of functionsallowing to modify "on-line" the content of the KB.Moreover, this release will integrate some new featuressuch as the possibility of doing some queries in theinterface and storing the selected entities in a new map.

At the end of our project (in 1996), there will be threeversions of APIC (figure 13). Basically, it will consist a library of functions allowing to display genomicsequences and to navigate in these sequences. This librarywill be organised in the form of an API (ApplicationProgramming Interface) allowing the other programmersto develop their specific interfaces. From this API, wewill implement two specific applications. First, anautonomous application that will be usable by all thebiologists ; this application (as the one presented in thispaper) will communicate with the user through a set offiles in the TINA format. Secondly, APIC will be amodule, fully integrated in our GREG project, allowing tovisualise and to modify the content of the KB.

Acknowledgements

We tliank all the members of the GREG project fortheir advices which allowed us to improve this interface.

ReferencesALTSCHUL S.F., GISH W., MII.LER W., MYERS E.W.,

LIPMAN D.J. 1990. Basic local alignment search tool.Journal of Mol. Biol., 215. 403-410.

BORODOVSKY M., MCININCH J.D. 1993. GENMARK:Parallel gene recognition for both DNA strands.Computers & Chemistry, 17(2).123-133.

CINKOSKY M. J. FICKETT J.W. 1992. SIGMA: Systemfor Integrated Genome Map Assembly, User’s Manual.Los Alamos. NM 87545. See also on the WWW,15RL http://www.ncgr.org/

DURBIN R., MIEG J.T. 1993. The ACeDB GenomeDatabase. WWW document, URLhttp://probe.nalusda.gov:8000/acedocs.

DURBIN R., MIEG J.T. 1992. - ACeDB - A C. ElegansDatabase 1. User’s Guide 2. System manual.

DOUTHART R.J., PELKEY J.E, THOMAS G.S. 1994. DataIntegration and Visualization of Maps of HumanGenome Using the GnomeView Interface. Proceedingsof 27th Annual Haw~ International Conference onSystem Sciences. 49-57.

FICHANT G., GAUTIER C. 1987. Statistical Method ForPredicting Protein Coding Regions In Nucleic AcidSequences. CABIOS vol.3, no.4. 1987. 287-295

ILOG 1994. Ilog Views Reference Manual. Version 2.1MARIlqO O., RECHENMANN F., UVIE’ITA P. 1990.

Multiple Perspectives and Classification Mechanismin Object-Oriented Representation. Proceedings of 9thEuropean Conference on Artificial Intelligence (ECAI).Stockholm. 425-430.

MgDIGUE C., VERMAT T, BISSON G., VIARI A.,DANCHIN A. In proceedings of ISMB 95. Cooperativecomputer system for genome sequence analysis.

MI~DIGUE C., WILLAMOWSKI J., CHEVENET F.,RECI-IENMANN F. 1993. Modeling tasks for problemsolving in molecular biology. Proceedings of theIJCAI’93 Workshop Artificial intelligence andgenome. Chambtry (France). pp 67-76.

RECHENMANN F., UVIETrA P. 1991. Shirka - An object-centered knowledge base management system. InArtificial Intelligence in Numerical and SymbolicSimulation, ALEAS Publ, Lyon.

WILLAMOWSKI J. 1994. Moddlisation de tdches pour lardsolution de probl~mes en coopdration syst~me-utilisateur. Ph.D. Thesis, Universit6 Joseph Fourier,Grenoble 1.

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