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revision 1.2, Tue Jan 25 03:02:07 2005 UTC revision 1.12, Tue Sep 13 03:50:59 2005 UTC
# Line 25  Line 25 
25                          the user's access codes must match this value.</Notes>                          the user's access codes must match this value.</Notes>
26                                          <DataGen>RandParam('low','medium','high')</DataGen>                                          <DataGen>RandParam('low','medium','high')</DataGen>
27                  </Field>                  </Field>
28                    <Field name="complete" type="boolean">
29                        <Notes>TRUE if the genome is complete, else FALSE</Notes>
30                    </Field>
31                          <Field name="taxonomy" type="text">                          <Field name="taxonomy" type="text">
32                                  <Notes>The taxonomy string contains the full taxonomy of the organism, while individual elements                                  <Notes>The taxonomy string contains the full taxonomy of the organism, while individual elements
33                                  separated by semi-colons (and optional white space), starting with the domain and ending with                                  separated by semi-colons (and optional white space), starting with the domain and ending with
# Line 33  Line 36 
36                                  <DataGen pass="2">join('; ', (RandParam('bacteria', 'archaea', 'eukaryote', 'virus', 'environmental'),                                  <DataGen pass="2">join('; ', (RandParam('bacteria', 'archaea', 'eukaryote', 'virus', 'environmental'),
37                                                                                            ListGen('PKVKVKVK', 5), $this->{genus}, $this->{species}))</DataGen>                                                                                            ListGen('PKVKVKVK', 5), $this->{genus}, $this->{species}))</DataGen>
38                          </Field>                          </Field>
39                    <Field name="group-name" type="name-string" relation="GenomeGroups">
40                        <Notes>The group identifies a special grouping of organisms that would be displayed on a particular
41                        page or of particular interest to a research group or web site. A single genome can belong to multiple
42                        such groups or none at all.</Notes>
43                    </Field>
44              </Fields>              </Fields>
45              <Indexes>              <Indexes>
46                  <Index>                  <Index>
# Line 93  Line 101 
101                                          <DataGen>RandChars("ACGT", IntGen(100,400))</DataGen>                                          <DataGen>RandChars("ACGT", IntGen(100,400))</DataGen>
102                                  </Field>                                  </Field>
103                  <Field name="quality-vector" type="text">                  <Field name="quality-vector" type="text">
104                                          <Notes>String describing the quality data for each . Individual values will                      <Notes>String describing the quality data for each base pair. Individual values will
105                                          be separated by periods. The value represents negative exponent of the probability                                          be separated by periods. The value represents negative exponent of the probability
106                                          of error. Thus, for example, a quality of 30 indicates the probability of error is                                          of error. Thus, for example, a quality of 30 indicates the probability of error is
107                                          10^-30. A higher quality number a better chance of a correct match. It is possible                                          10^-30. A higher quality number a better chance of a correct match. It is possible
108                                          that the quality data is known for a sequence. If that is the case, the quality                      that the quality data is not known for a sequence. If that is the case, the quality
109                                          vector will contain the [b]unknown[/b].</Notes>                                          vector will contain the [b]unknown[/b].</Notes>
110                                          <DataGen>unknown</DataGen>                                          <DataGen>unknown</DataGen>
111                                  </Field>                                  </Field>
# Line 114  Line 122 
122                                          <DataGen>RandParam('peg','rna')</DataGen>                                          <DataGen>RandParam('peg','rna')</DataGen>
123                                  </Field>                                  </Field>
124                  <Field name="alias" type="name-string" relation="FeatureAlias">                  <Field name="alias" type="name-string" relation="FeatureAlias">
125                                          <Notes>Alternative name for this feature. feature can have many aliases.</Notes>                      <Notes>Alternative name for this feature. A feature can have many aliases.</Notes>
126                                          <DataGen testCount="3">StringGen('Pgi|99999', 'Puni|XXXXXX', 'PAAAAAA999')</DataGen>                                          <DataGen testCount="3">StringGen('Pgi|99999', 'Puni|XXXXXX', 'PAAAAAA999')</DataGen>
127                                  </Field>                                  </Field>
128                  <Field name="translation" type="text" relation="FeatureTranslation">                  <Field name="translation" type="text" relation="FeatureTranslation">
129                                          <Notes>[i](optional)[/i] A of this feature's residues into character codes, formed by concatenating                      <Notes>[i](optional)[/i] A translation of this feature's residues into character
130                          the pieces of the feature together.</Notes>                      codes, formed by concatenating the pieces of the feature together. For a
131                        protein encoding group, this is the protein characters. For other types
132                        it is the DNA characters.</Notes>
133                                          <DataGen testCount="0"></DataGen>                                          <DataGen testCount="0"></DataGen>
134                                  </Field>                                  </Field>
135                  <Field name="upstream-sequence" type="text" relation="FeatureUpstream">                  <Field name="upstream-sequence" type="text" relation="FeatureUpstream">
# Line 128  Line 138 
138                                          <DataGen testCount="0"></DataGen>                                          <DataGen testCount="0"></DataGen>
139                                  </Field>                                  </Field>
140                  <Field name="active" type="boolean">                  <Field name="active" type="boolean">
141                                          <Notes>TRUE if this feature is still considered valid, if it has been logically deleted.</Notes>                      <Notes>TRUE if this feature is still considered valid, FALSE if it has been logically deleted.</Notes>
142                                          <DataGen>1</DataGen>                                          <DataGen>1</DataGen>
143                                  </Field>                                  </Field>
144                                  <Field name="link" type="text" relation="FeatureLink">                                  <Field name="link" type="text" relation="FeatureLink">
# Line 139  Line 149 
149                                          "&amp;Number=" . IntGen(1,99)</DataGen>                                          "&amp;Number=" . IntGen(1,99)</DataGen>
150                                  </Field>                                  </Field>
151              </Fields>              </Fields>
152                <Indexes>
153                    <Index>
154                        <Notes>This index allows the user to find the feature corresponding to
155                        the specified alias name.</Notes>
156                        <IndexFields>
157                            <IndexField name="alias" order="ascending" />
158                        </IndexFields>
159                    </Index>
160                </Indexes>
161          </Entity>          </Entity>
162          <Entity name="Role" keyType="string">          <Entity name="Role" keyType="string">
163              <Notes>A [i]role[/i] describes a biological function that may be fulfilled by a feature.              <Notes>A [i]role[/i] describes a biological function that may be fulfilled by a feature.
# Line 166  Line 185 
185                                  </Field>                                  </Field>
186              </Fields>              </Fields>
187          </Entity>          </Entity>
188          <Entity name="Subsystem" keyType="name-string">          <Entity name="Subsystem" keyType="string">
189              <Notes>A [i]subsystem[/i] is a collection of roles that work together in a cell. Identification of subsystems              <Notes>A [i]subsystem[/i] is a collection of roles that work together in a cell. Identification of subsystems
190              is an important tool for recognizing parallel genetic features in different organisms.</Notes>              is an important tool for recognizing parallel genetic features in different organisms.</Notes>
191          </Entity>          </Entity>
# Line 251  Line 270 
270                                          </Field>                                          </Field>
271                                  </Fields>                                  </Fields>
272                  </Entity>                  </Entity>
273            <Entity name="Coupling" keyType="medium-string">
274                <Notes>A coupling is a relationship between two features. The features are
275                physically close on the contig, and there is evidence that they generally
276                belong together. The key of this entity is formed by combining the coupled
277                feature IDs with a space.</Notes>
278                <Fields>
279                    <Field name="score" type="int">
280                        <Notes>A number based on the set of PCHs (pairs of close homologs). A PCH
281                        indicates that two genes near each other on one genome are very similar to
282                        genes near each other on another genome. The score only counts PCHs for which
283                        the genomes are very different. (In other words, we have a pairing that persists
284                        between different organisms.) A higher score implies a stronger meaning to the
285                        clustering.</Notes>
286                    </Field>
287                </Fields>
288            </Entity>
289            <Entity name="PCH" keyType="string">
290                <Notes>A PCH (physically close homolog) connects a clustering (which is a
291                pair of physically close features on a contig) to a second pair of physically
292                close features that are similar to the first. Essentially, the PCH is a
293                relationship between two clusterings in which the first clustering's features
294                are similar to the second clustering's features. The simplest model for
295                this would be to simply relate clusterings to each other; however, not all
296                physically close pairs qualify as clusterings, so we relate a clustering to
297                a pair of features. The key is the clustering key followed by the IDs
298                of the features in the second pair.</Notes>
299                <Fields>
300                    <Field name="used" type="boolean">
301                        <Notes>TRUE if this PCH is used in scoring the attached clustering,
302                        else FALSE. If a clustering has a PCH for a particular genome and many
303                        similar genomes are present, then a PCH will probably exist for the
304                        similar genomes as well. When this happens, only one of the PCHs will
305                        be scored: the others are considered duplicates of the same evidence.</Notes>
306                    </Field>
307                </Fields>
308            </Entity>
309      </Entities>      </Entities>
310      <Relationships>      <Relationships>
311            <Relationship name="ParticipatesInCoupling" from="Feature" to="Coupling" arity="MM">
312                <Notes>This relationship connects a feature to all the functional couplings
313                in which it participates. A functional coupling is a recognition of the fact
314                that the features are close to each other on a chromosome, and similar
315                features in other genomes also tend to be close.</Notes>
316                <Fields>
317                    <Field name="pos" type="int">
318                        <Notes>Ordinal position of the feature in the coupling. Currently,
319                        this is either "1" or "2".</Notes>
320                    </Field>
321                </Fields>
322                <ToIndex>
323                    <Notes>This index enables the application to view the features of
324                    a coupling in the proper order. The order influences the way the
325                    PCHs are examined.</Notes>
326                    <IndexFields>
327                        <IndexField name="pos" order="ascending" />
328                    </IndexFields>
329                </ToIndex>
330            </Relationship>
331            <Relationship name="IsEvidencedBy" from="Coupling" to="PCH" arity="1M">
332                <Notes>This relationship connects a functional coupling to the physically
333                close homologs (PCHs) which affirm that the coupling is meaningful.</Notes>
334            </Relationship>
335            <Relationship name="UsesAsEvidence" from="PCH" to="Feature" arity="MM">
336                <Notes>This relationship connects a PCH to the features that represent its
337                evidence. Each PCH is connected to a parent coupling that relates two features
338                on a specific genome. The PCH's evidence that the parent coupling is functional
339                is the existence of two physically close features on a different genome that
340                correspond to the features in the coupling. Those features are found on the
341                far side of this relationship.</Notes>
342                <Fields>
343                    <Field name="pos" type="int">
344                        <Notes>Ordinal position of the feature in the coupling that corresponds
345                        to our target feature. There is a one-to-one correspondence between the
346                        features connected to the PCH by this relationship and the features
347                        connected to the PCH's parent coupling. The ordinal position is used
348                        to decode that relationship. Currently, this field is either "1" or
349                        "2".</Notes>
350                    </Field>
351                </Fields>
352                <FromIndex>
353                    <Notes>This index enables the application to view the features of
354                    a PCH in the proper order.</Notes>
355                    <IndexFields>
356                        <IndexField name="pos" order="ascending" />
357                    </IndexFields>
358                </FromIndex>
359            </Relationship>
360          <Relationship name="HasContig" from="Genome" to="Contig" arity="1M">          <Relationship name="HasContig" from="Genome" to="Contig" arity="1M">
361              <Notes>This relationship connects a genome to the contigs that contain the actual genetic              <Notes>This relationship connects a genome to the contigs that contain the actual genetic
362              information.</Notes>              information.</Notes>
# Line 353  Line 457 
457                  </IndexFields>                  </IndexFields>
458              </ToIndex>              </ToIndex>
459          </Relationship>          </Relationship>
         <Relationship name="IsClusteredOnChromosomeWith" from="Feature" to="Feature" arity="MM">  
             <Notes>This relationship is one of two that relate features to each other. It connects  
             features that are physically close to each other on a single chromosome.</Notes>  
             <Fields>  
                 <Field name="score" type="int">  
                         <Notes>The number of co-occurrences in genomes that are not  
                         extremely closely-related.</Notes>  
                 </Field>  
             </Fields>  
         </Relationship>  
460          <Relationship name="IsBidirectionalBestHitOf" from="Feature" to="Feature" arity="MM">          <Relationship name="IsBidirectionalBestHitOf" from="Feature" to="Feature" arity="MM">
461              <Notes>This relationship is one of two that relate features to each other. It              <Notes>This relationship is one of two that relate features to each other. It
462              connects features that are very similar but on separate genomes. A              connects features that are very similar but on separate genomes. A

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