Ocelot is a frame representation system implemented on top of Common Lisp. It can be thought of as an object-oriented database. Please see the following for more discussion on frame representation systems The Design Space of Frame Knowledge Representation Systems.
It performs an analogous role as the SQL language performs for different relational databases. There are certain terms that are used when describing objects, meta-objects, and relationships in a frame system. Much of the terminology is similar to the concepts from object oriented design. Here we provide definitions for the most common occurrences.
In the application code level, there are certain functions that have been identified as being useful for end-users as well. The Pathway Tools schema is the particular collection of classes, and the defined relationships between them, that are present in the knowledgebase of any PGDB. Ocelot supports multiple inheritance of classes, so a class or instance might have more than one direct superclass.
It is highly recommended to perform any desired addition of classes via the Pathway Tools Navigator if possible, or through the GKB Editor. Please see the Ocelot and GFP documentation for more information. Some functions allow you to provide an optional argument, where you can specify which organism you wish to have the function run against. This section lists a series of functions that are used for convenient navigation from one object type to another, such as from biochemical pathways to their constituent reactions, or from DNA binding sites to regulation description objects.
Unless otherwise specified, it should be assumed that all of these functions apply only to the currently selected PGDB. This file contains the following sections:. You may use this box to search for genes, proteins, compounds, RNAs, reactions, pathways, operons, and GO terms. If the query string matches a single object, the page for that object will be displayed immediately. If there are multiple matches, the full list of matches will be shown, organized by the type of object e.
Some examples of what can be entered into the Quick Search box include:. The name of a compound, gene, protein, pathway or other object.
Spaces, punctuation and capitalization are ignored. An object will be returned if the query string matches either its common name or one of its synonyms. Examples: pyruvate, trpA. Any substring of one of the above names that is 3 or more characters in length. Examples: kinase, pyr. A compound InChI-key full or partial. A PGDB internal object identifier for any compound, gene, protein, pathway, reaction, transcription-unit or schema class.
Correct capitalization may be required. An identifier from some external database to which we maintain links, e. Correct capitalization and punctuation is required. Note that our set of links is not complete — just because a search for an external ID returns no result does not mean that we do not have the object in our database.
To match several words or text-fragments simultaneously, type in the words separated by spaces to find an object with all the words in its name, or separated by commas to find objects with any of the words in its name.
For example, if you enter nitrate camphor , the program will search for a single object that has both nitrate and camphor in its name. However, entering nitrate, camphor would result in a search for objects which have either nitrate or camphor in their names. If your query text is one or two characters in length, only exact text matches will be returned because of the many matches that would otherwise result. For longer text fragments, the search will return all objects that contain the text rather than match it exactly.
In the example given, assuming the current organism is E. With the qualifier you will be taken directly to the trpa gene page. With the qualifier, just the seven compounds with ATP in the name will be returned. Allowable type-qualifiers include pathway , gene , enzyme , rna , go-terms , compound , reaction , operon , and organism. Each such page contains options for searching using a number of different criteria, either individually or in combination.
When the page is initially loaded, only the name searches are active, but by clicking on the different search bars, you can enable or disable additional search criteria.
If multiple search criteria are specified for a given search, then unless otherwise specified the results must satisfy all of them that is, an AND connector is used to combine the different criteria. The results of all object searches is a table containing the names of all objects that satisfy the search, with hyperlinks to their corresponding data pages, along with any additional columns relevant to the particular search.
The table will initially be sorted alphabetically by name, but small triangles in the column headers allow the user to sort by any column, in either ascending or descending order. The sections below describe the different search criteria that are available for each object type. The software will attempt to do auto-completion on the string you have entered based on the contents of the database. If you select one of the auto-complete options, then when you submit the form you will be taken directly to the data page for the selected gene, regardless of any other search criteria you may have specified i.
If you do not select one of the auto-complete options, then the string you typed will be the target of a substring search, which may be combined with other search criteria. The software will attempt to do auto-completion, as for the gene name field. If either the minimum or maximum field is left blank, then the sequence length is unconstrained in that direction. The results will include any gene that overlaps any portion of the specified region. If either the minimum or maximum field is left blank, then the map position is unconstrained in that direction.
If the selected organism has multiple replicons, then this search option will include a checkable list of replicons — you may select one or more replicons either instead of or in conjunction with the map position in order to constrain the search to genes on a particular replicon. Enter the name of a small molecule. We recommend taking advantage of the auto-complete facility to select the correct small molecule, as only an exact match to a compound name can be accepted here.
Check all roles that you are interested in for this compound. Note that we consider cofactors to include only compounds that are not modified in any way during the reaction. Molecules such as NAD, which are modified, are considered to be substrates, not cofactors. Relatively little information about activators, inhibitors, etc. Each evidence code includes in parentheses after its name the number of gene products that have their function annotated with that code.
Selecting one or more codes to filter on allows you to restrict your search, for example, to all proteins whose function has been established experimentally. The Pathway Tools evidence codes and ontology are described here. Selecting one or more components allows you to restrict your search to proteins known to be present in those cellular locations. Note that relatively little information about cellular locations of gene products is available for databases other than EcoCyc or MetaCyc.
The Pathway Tools cell component ontology is described here. Only terms that have one or more gene products annotated to them or their children will be present, and the number in parentheses after each term name indicates the number of gene products annotated to that term or one of its children.
You may browse this ontology to a particular term to see all gene products annotated with that term. Clicking on a gene product will then take you directly to the data page for that gene product, just as clicking on a term name will take you to the data page for that term. Alternatively, you can use the checkboxes to indicate that your search should be restricted to include only gene products annotated with the checked terms or their children.
If you wish to filter by only a single term, and you know the name or ID for that term, you also have the option of typing it in the text box using auto-completion to ensure you select the correct term. Select one or more GO evidence codes to restrict the search results to GO term matches with one of the selected evidence codes. Only terms that have one or more genes annotated to them or their children will be present, and the number in parentheses after each term name indicates the number of genes annotated to that term or one of its children.
You may browse this ontology to a particular term to see all genes annotated with that term. Clicking on a gene will then take you directly to the data page for that gene, just as clicking on a term name will take you to the data page for that term.
Alternatively, you can use the checkboxes to indicate that your search should be restricted to include only genes annotated with the checked terms or their children. Enter either the PubMed ID, the author surname, or part or all of an article title. Select one or more feature types to search for proteins annotated with those features. If you select one of the auto-complete options, then when you submit the form you will be taken directly to the data page for the selected compound, regardless of other search criteria you may have specified i.
Each compound class includes in parentheses after its name the number of instance-level compound objects that are members of that class. The ontology may be used in one of two ways. Alternatively, you can check the checkbox next to one or more class names to limit your search which may also include other search criteria so as to only include compounds that belong to one of the checked classes.
If either the minimum or maximum field is left blank, then the molecular weight is unconstrained in that direction.
If an element symbol is followed by a number, then only compounds with exactly that number of that element in its chemical formula will be included in the result.
For example, the query string C12N will retrieve all compounds with exactly 12 carbons, one or more nitrogens, and possibly some other elements. The search is case-insensitive unless case is needed to disambiguate. For example, either co or CO will retrieve all compounds containing both carbon and oxygen, but Co will instead retrieve all compounds containing cobalt.
We support only exact string matching for InChI strings. You may enter either the full InChI key, or a partial InChI key that omits either the charge or the isomer and charge information.
Search for reaction by EC number or name Enter a reaction EC number or name typically an enzyme name. EC numbers can be either full or partial. The software will attempt to do auto-completion on the name or EC number. If you select one of the auto-complete options, then when you submit the form you will be taken directly to the data page for the selected reaction or reaction class, regardless of any other search criteria you may have specified i.
When multiple compounds are specified, they can appear anywhere in the reaction equation, or they can be restricted to being on either the same or opposite sides of the reaction relative to each other.
We recommend taking advantage of the auto-complete facility to select the correct compound, as only an exact match to a compound name can be accepted here. Each reaction class includes in parentheses after its name the number of reactions that are members of that class.
Alternatively, you can check the checkbox next to one or more class names to limit your search which may also include other search criteria so as to only include reactions that belong to one of the checked classes.
Note that there are two parallel reaction classification systems, one in which reactions are classified by conversion type this includes the entire EC hierarchy , and another in which the reactions are classified by substrate.
Most reactions in the database have parents in both classification systems. Transport reactions will not be included. If you select one of the auto-complete options, then when you submit the form you will be taken directly to the data page for the selected compound. This is true regardless of any other search criteria you may have specified i. Each pathway class includes in parentheses after its name the number of reactions that are members of that class.
Alternatively, you can check the checkbox next to one or more class names to limit your search which may also include other search criteria so as to only include pathways that belong to one of the checked classes. If either the minimum or maximum field is left blank, then the number of reactions is unconstrained in that direction.
If you enter more than one compound, then the pathway must involve all specified compounds in order to be included in the results. Each evidence code includes in parentheses after its name the number of pathways that have their function annotated with that code.
Selecting one or more codes to filter on allows you to restrict your search, for example, to all pathways whose presence has been established experimentally. The fact that a pathway is not stated to be present in a given organism does not mean that the organism does not have the pathway — pathways are curated for only a small subset of the organisms in which they appear.
Each pathway in MetaCyc has been annotated with its expected taxonomic range. This search option allows you to restrict your search to include only those pathways you could reasonably expect to see for a given taxonomic grouping, for example, to restrict your search to pathways seen in plants.
The kinds of sites that can be searched here include transcription units, promoters, terminators, transcription-factor binding sites, riboswitches, REP elements, transposons, phage attachment sites, etc.
You must specify at least one site type. The results will include any site that overlaps any portion of the specified region. If the selected organism has multiple replicons, then this search option will include a checkable list of replicons — you may select one or more replicons either instead of or in conjunction with the map position in order to constrain the search to sites on a particular replicon.
Use the autocomplete functionality to select a full name, as no substring matching is done on the regulator name. If no match is found, then the database contains no regulatory interactions or sites involving that regulator.
This filter is compatible only with searches for transcription units, promoters, transcription factor binding sites, attenuators, or mRNA binding sites.
Selecting one or more codes to filter on allows you to restrict your search, for example, to all promoters whose location has been established experimentally. Some databases may include sets of growth media, along with information about whether or not the organism can grow on a particular medium and under what conditions for example, gene knockout studies can indicate whether the organism can grow on a particular medium in the absence of a particular gene.
To see the full list of growth media for a database, including an indication of which media have associated knockout data, click on the All Growth Media for this Organism button. Use the other fields of this form to search for growth media that meet certain criteria.
Search for growth media by name Enter a growth medium name or name fragment. If no gene knockout is specified, then the growth levels refer to wildtype growth. If a gene is specified, then the growth levels refer to knockouts of that gene. When specifying a gene, we recommend using the auto-complete facility to select the correct gene, as only an exact name match can be accepted here. Some databases include DNA or mRNA sites that are not genes, such as transcription-units, promoters, terminators, binding-sites, extragenic-sites, etc.
This page includes a checklist of all types of such sites that are present in the current database. Select one or more types that you wish to search. The other fields of this form allow you to further constrain your search. As you start typing in the textbox, a menu of possible completions will appear. This menu will only include proteins and RNAs that are known to regulate transcription or translation — you must select the appropriate value from the auto-complete menu.
The small molecule can bind directly to or otherwise directly regulate a site as in the case of riboswitches , or can bind to a transcription factor to either enable or prevent it from binding to a site. This menu will only include small molecules that are known to regulate transcription or translation — you must select the appropriate value from the auto-complete menu. The Advanced Search tool facilitates generation of queries that are more complex than those supported by the object search tools described above.
Using the Advanced Search tool, you can write queries that combine data from multiple organisms or multiple types of objects, and you can search fields that are not supported by the individual object search pages. Detailed instructions for using the Advanced Search tool to construct complex queries are available here.
It enable queries across all the organisms on the BioCyc. Search Terms Enter the term s you wish to search for. Also, if you enter multiple terms, you can select whether all terms must be present, or just any one or more of them.
The latter will be possibly less useful. Choose Organisms You can choose a set of organisms individually by name or property. You can also select all members of a taxonomically-related group, for example all Bacteria. Search results are presented sorted by relevance or match strength in a table with clickable links, which link to the details for each matched entity.
Each column in the table can be used to sort the results, with the relevance being used as the default. Re-sorting the table re-sorts all of the results, and this sorting is preserved as you navigate through the results table, from one page to the next. This facility not available for MetaCyc allows you to perform sequence-similarity searches using the BLAST program to compare your protein or nucleic acid sequence against the complete genome of the selected organism database.
Searches will not be restricted to the selected database, and can locate text strings found in page comments, help pages, and other page content not queryable by other means.
Submitting this form will direct the user outside this Web site to a page generated by Google. A Google full text search is also offered as an option when a Quick Search fails to return any result or does not return the desired result. Textpresso is a package for indexing and searching a corpus of biological literature. Textpresso searches are available for searching a large Escherichia coli literature corpus only at the BioCyc Web site, and are available only when EcoCyc is the selected database.
An ontology is a carefully constructed vocabulary of terms, often called a controlled vocabulary. The terms are organized into a classification hierarchy also called a taxonomy. Ontologies can be used to browse and search for objects by drilling down from more general categories to more specific ones.
Those that can be searched are available from the Ontologies sub-menu in the Search menu. These ontologies can also be accessed from the object search page for their particular object type. The browseable ontologies are:. Each database only contains those terms to which one or more gene products are actually assigned, so a term may be missing from the browseable ontology even though it is a valid GO term.
Define SmartTables of genes, pathways, metabolites, and more for analysis and to share with colleagues. If those words are missing it probably means that Web Accounts are not enabled for this Pathway Tools Web site.
The genome browser can be used to examine one replicon chromosome or plasmid at a time. Its tracks capability can be used to visualize high-throughput datasets in a genome context. At the top of the genome-browser page, the full length of the chromosome is shown at low resolution. A region of the chromosome can be selected for display at much higher magnification in the lower part of the screen. The selected region will be drawn using as many lines as will comfortably fit on the Web browser page.
The full chromosome view at the very top indicates the magnified region by means of a red, rectangular cursor. Clicking on a vertical tick mark within the full chromosome line at the top will show the immediate neighborhood of that position. The tick marks in the magnified region can also be clicked on, to recenter the region around the selected tick mark quickly. Start and end base-pair positions can be entered in the corresponding text entry boxes; clicking the Go button displays that region.
The region around a gene can be shown by entering the gene name in the corresponding text entry box and clicking on the Go button. The selected gene will be visually highlighted. The panel of navigation arrows to the left of the legend can be used for moving to a nearby region. The panel allows lateral translation to the left or right, and also serves to zoom in or out. ORFs for actual or inferred proteins have symmetrical arrowheads with the arrow apex in the center , whereas RNA genes have an asymmetrical arrowhead with the apex at the top edge.
Phantom- and pseudo-genes are crossed out with a big, diagonal X. When a gene wraps across more than one line, a zigzag at the end of the line indicates that the gene continues on the next line. Clicking on a gene brings up the corresponding gene description page. Gene arrows filled with solid colors have transcription unit operon information available. All the adjacent genes that are part of a given operon are assigned the same color.
Genes that have not been assigned to any transcription unit are not colored. Additionally, transcription-units are indicated by a gray background area behind the genes, spanning the entire region of the operon. Moving the mouse-cursor over the genes reveals their product name and the length in base pairs of the intergenic region between the chosen gene and its neighboring genes to the left and right.
If the number of base pairs carries a minus sign, the genes overlap by that many bases. As an example:. This means that there are 11 bp to the left of xdhB before xdhA is reached, but to the right, xdhC overlaps with xdhB by 3 bp. If the overlap between adjacent genes is more than a small amount, the shorter gene is drawn above the longer gene to avoid visual clashes.
When zooming in to a great level of detail, transcription start sites and terminators are drawn. Moving the mouse-cursor over a transcription start site reveals the operon it is part of. The transcription factors controlling the operon are also shown, with a plus sign meaning activation and a minus sign meaning inhibition. Clicking on a transcription start site brings up the corresponding transcription unit description page.
External datasets can be shown alongside the display of a replicon region, in form of additional tracks that are uploaded by the user. The supported tracks file format is GFF, version 2. The GFF file allows definition of segments on the chromosome that are denoted by a start and stop base-pair position. In an attribute field of the file, a name can be assigned to the segment, and in a score field, a numerical value such as an expression value can be supplied. This allows a broad range of different data types to be shown in the genome browser, aligned with the genes and transcription units that a PGDB already describes.
This could include alternate gene predictions, or the results of expression experiments. Each specified segment can state a source and feature value, allowing different segment types to be supplied in one file. If in these groups some of the shown segments overlap due to their base-pair positions, such horizontal segments will be displayed on separate lines, to avoid visual clashes.
To view data from such a GFF file in an external track, first open the genome browser. This will enter the external tracks mode, in which the magnified genome region will no longer wrap to fill the screen, instead making room for external tracks that will be displayed underneath. Vertical hair lines will be shown for easier visual alignment of features in external tracks with the magnified region.
Next, add tracks data from an external data file using the controls at the bottom of the page. Depending upon the size of your GFF file, it can take several minutes to upload a file. During this time, the page will not respond, and you should not click more controls. After the file has finished successfully uploading and being parsed, it will let you know by refreshing the page. Following the display of a track, you can continue to browse the genome normally, using the standard Left, Right, Zoom Out, and Zoom In controls, and the Gene Name box.
You can display data from more than one GFF file at the same time. Load each file individually using the procedure described above. Tracks from the first file loaded will appear just below the gene line. Tracks from the second file loaded will appear below those from the first, and so on. The order of the tracks can be changed, by left-clicking on the underlined track titles on the left side, which name the feature type.
The popup menu allows the chosen track to be moved up or down by one step relative to the current ordering. The horizontal bars represent the feature data found in the GFF track file. These are arranged in rows distributed vertically, so as to help prevent overlapping features from running into each other and being indistinguishable.
The number of distributed rows may vary with the zoom scale, so that features can fit; there is no other meaning to the number of lines. The length of each horizontal bar shows the extent of each individual feature reading. The color is drawn from a spectrum that shows the magnitude of a score. In order to get a better feel for this magnitude, a graph of the same track feature data is also plotted above the horizontal bars.
The magnitude of the score is represented as the height on the graph. This offers an intuitive method of viewing trends and anomalies in the data at a glance. This is useful for features that tend to be very short, which may otherwise be hard to see. It is possible to choose to display, or turn off the display, of either the horizontal bars or the graph plot or both, for each of multiple tracks viewed simultaneously.
This control allows you to stack graphs from different tracks close to each other, so that you can compare them and see fine differences between them. It is also possible to shift the plotted range of this graph for each track file viewed. Entries may be in integers or decimals. The lower range must be less than the upper range coordinate.
Score values that fall outside the range will result in the display of a horizontal line just a little bit outside the graph range, to visually indicate this over- or underflow condition. In graph mode, the entire track is assigned a color from a predefined set of colors. However, it is possible for the user to choose the color of a track, by adding a new header comment line close to the top of the GFF file, before uploading the file.
An example line looks like this:. The comparative genome browser can be used to examine several replicons chromosomes or plasmids simultaneously, side by side. This view facilitates comparison of related organisms to observe similarities and differences in their gene arrangements. For the alignment to work, ortholog links must exist among genes of the organisms to be compared. The comparative genome browser is usually entered from a page describing a gene. To invoke it, select Align in Multi-Genome Browser from the operations box on the right side of the page.
You will first be asked to specify the organisms whose genome regions you wish to compare. The selected set of organisms is remembered for some time by the Web browser. When the comparative genome browser is invoked from a gene page, that gene and its organism orchestrate the rest of the alignment. In the display, the top-most replicon is the reference, against which the comparisons are made by following the ortholog links for every gene of the top replicon in its visible section.
The selected gene that is the focus of the comparison is highlighted on each replicon by a thick outline and a slanted hashed background. These selected genes are lined up at the center position of their lengths. The magnified region can be adjusted by the following methods:. The panel of navigation arrows can be used to translate the view left or right, and to zoom in and out. Genes with solid colors have links to orthologs.
Corresponding orthologs are assigned the same color, out of a set of a dozen colors that will be reused repeatedly. Genes for which no ortholog links were found in the PGDB are not colored. The other display features are the same as described for the regular genome browser. A SmartTable is a collection of PGDB objects, such as genes or pathways, together with associated data, that can be displayed in tabular form. SmartTables can be created from tabular data files, and from query results, and SmartTables can be exported to files.
Transformations, filtering, and set operations on SmartTables can be performed. Example transformations include:. Transform a SmartTable of genes to a SmartTable of promoters, or transcription binding sites, or transcriptional regulators, that control those genes.
Transform a SmartTable of pathways to a SmartTable of metabolites that are substrates in the pathway. SmartTables can be private, public, or shared with a selected SmartTable of users. Firefox is the recommended browser to use with SmartTables. Other browsers will work but have not been as thoroughly tested with SmartTables and thus minor issues may arise. Use of Internet Explorer is discouraged, but, for the most part, will work as well.
A number of SmartTables operations can also be invoked via web services. Some terminology: A SmartTable consists of a set of rows and columns. A cell is the intersection of a row and a column, and can contain one or more values , which may be Pathway Tools objects such as genes or pathways , numbers, or strings.
A SmartTable is displayed on its own web page see the figure below. The URL of this page is persistent and may be bookmarked or shared.
At the top of this page are some metadata about the SmartTable, such as its title and a textual description these can both be edited by clicking on them. In this example, we started with a SmartTable of genes in the first column after the checkboxes , and added some properties. The blue column headings are clickable and can be used to select individual columns for certain operations. A SmartTable must always contain at least one column.
If a SmartTable has more elements than will fit on a page, paging controls will be displayed above the column headings.
All rows can also be dispalyed on one page. Note that checkboxes work properly over multiple pages — that is, some rows can be checked, a new page can be navigated to and check some more, and the ones on the first page will still be considerered checked.
This checkbox behavior also applies to any lists of SmartTables. The SmartTable directory page provides a list of accessible SmartTables. It may be accessed via any of the items under the SmartTables menu. The directory is composed of several tabs:.
All SmartTables — a list of all accessible SmartTables. Special SmartTables — a list of computed SmartTables, based on the currently selected organism. By default the SmartTable directory is ordered by update time most recently changed first , but it can be resorted using the sort arrows in column headings.
There are a number of ways to create a SmartTable. The results of web searches e. This creates a SmartTable with a single column and no rows. The row has an autocompleting text field. Enter an object name e. To turn them into recognized database objects e.
A SmartTable can be created by importing a text file that specifies the coordinates of replicon regions, and associated sequence variants, in a tab-separated file format. A special transformation supports further analysis and interpretation of sequence-variant data — see Section 6. Replicons can be specified in the file by either frame name or common name. Nucleotide coordinates for the start and end positions are relative to the replicon specified. If only either a start or end position is given, it is defined as a single nucleotide region.
The resulting SmartTable will contain either one or two columns — the first column will contain the specified regions; the second column will contain region comments, if supplied; see example below. Clicking on a cell in the first column will open the genome browser around that region. There are a number of ways to create new SmartTables from existing SmartTables. See also the Filtering operation which has the option of creating a new SmartTable based on a filtered subset of rows.
SmartTables can be manipulated in a large number of ways, both at a fine level of granularity such as editing individual cells , and by applying transformations to an entire SmartTable. Property columns show attributes slot values of an object, such as the molecular weight of a compound or the pI of a protein.
The most common situation is to add a property column for the objects listed in the first column of the SmartTable, but the Add Property Column dropdown menu will list available properties to show for the currently selected column.
The ability to create a property column or an enrichment column from another property column may not be available. Editable columns which are those that are not defined by a transform or other computation can be edited by clicking the edit icon in the column header. This changes the cells to editable fields.
Clicking the icon a second time will turn off editing for that column. Any editable cells in the new row are displayed in edit mode, so values can be entered. These operations apply to the selected column.
This icon will not be present if deleting the column is not currently a valid action, such as when the SmartTable has only one column. SmartTables can be resorted on the values of any column by means of the sorting controls triangles in column headers. Filtering means selecting a subset of rows from a SmartTable according to some criterion.
To learn more about Azure Synapse Pathway, see behind the scenes for a step-by-step process on how Azure Synapse Pathway works. To install Synapse Pathway, check Azure Synapse Pathway download for pre-requisites and the link to download the latest version. Azure Synapse Pathway supports code conversion of database, schemas, and tables for the following sources:.
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