专利汇可以提供SCIENTIST DOMAIN-CENTRIC USER INTERFACE AND ENABLING "SOFT" TRANSLATION专利检索,专利查询,专利分析的服务。并且The scientist domain-centric user interface system may prompt the user to supply scientist-centric information expressed utilizing terminology of a scientific domain, such as biology or analytical chemistry. A translation system then generates control parameters to control the search algorithm, thus relieving the user from having to learn how select and configure the algorithm control parameters directly.,下面是SCIENTIST DOMAIN-CENTRIC USER INTERFACE AND ENABLING "SOFT" TRANSLATION专利的具体信息内容。
What is claimed is:
This application claims the benefit of U.S. Provisional Application No. 60/696,077, filed on Jun. 30, 2005. The disclosure of the above application is incorporated herein by reference.
Mass spectrometry is one of the major analytical techniques for identification of proteins and for conducting other life sciences experiments. Mass spectrometry instruments produce data that can be quite complex, often requiring sophisticated software to analyze the raw mass spectral data. Current industry standard software employ complex and somewhat arcane parameters that are not well understood by scientists working in the laboratory.
As more fully set forth herein, a scientist domain-centric user interface system may prompt the user to supply scientist-centric information expressed utilizing terminology of a scientific domain, such as biology or analytical chemistry. A translation system then generates control parameters to control the search algorithm, thus relieving the user from having to learn how select and configure the algorithm control parameters directly.
These and other features of the present teachings are set forth herein. Further areas of applicability will become apparent from the description provided herein. It should be understood that the description and specific examples are intended for purposes of illustration only and are not intended to limit the scope of the present disclosure.
The skilled artisan will understand that the drawings, described below, and the XLM file listings provided in the Appendices, are for illustration purposes only. The drawings and listings are not intended to limit the scope of the present teachings in any way.
The following description is merely exemplary in nature and is not intended to limit the present disclosure, application, or uses. It should be understood that throughout the drawings, corresponding reference numerals indicate like or corresponding parts and features.
One of the main workflows currently used is the digestion of a protein sample with a reagent, which cleaves the full proteins into smaller peptides that are then easier to identify. Thus for illustration purposes, an exemplary workflow involving digestion of a protein sample has been illustrated in
For example, the user interface and translation techniques described herein might be applied in a workflow that looks at endogenously occurring peptides (ones that are isolated from natural in vivo digestion, rather than the result of intentional digestion as part of a workflow). Also, while the exemplary workflow illustrated in
Referring to
Because of the sophistication of the pattern matching problem, and because of the highly complex nature of the raw mass spectrometry data, present day search algorithms require the user to make a number of parameter settings before the search algorithm is invoked. While some of the search parameters may be familiar to the typical user, unfortunately many are arcane. Thus, with conventional informatics search tools the user needs a great deal of experience, familiarity with current informatics publications describing the use of these tools, as well as a reasonable high mathematical and statistical skill level, and outright experimentation with the tools in order to know the optimal search parameter settings for a given experiment. This has, unfortunately, placed the use of mass spectrometry instruments and informatics search tools beyond the reach of many good biologists who would use these tools for protein research,
To solve this problem, the scientist domain-centric user interface and enabling “soft” translation system provides a specially designed user interface 26 and an associated translation layer 28 that allows the user 30 to set the search parameters for the search algorithm 24 without having any special knowledge of the informatics search tool as would conventionally be required. As will be more fully described, the user interface provides controls for protein identification software that have no parameters that would not be well understood by a novice user. This is accomplished by configuring the user interface to be in the language of the scientists' domain, with the translation layer 28 converting the user's instructions into the language of the search algorithm domain.
Referring to
Another example of a parameter that would invite arbitrary settings involves the complicated issue of setting mass tolerances for database search methods. An expert would have a statistical sense of what effect the MS and the MS/MS tolerance will have on discrimination, false negatives, and search time, and the expert will also appreciate how to take into consideration the particular qualities of the instrument that produced the data. Unfortunately, the average scientist performing biological research would have no understanding of these issues and would thus need to resort to a great deal of experimentation in order to finally arrive at the optimal settings for a given type of data.
The user interface 25 (
Similarly, user interface 26 includes a region where the user can supply information about processing (what the user wants to know). These topics are set forth in the area designated “Special Processing” and include the following: Quantitate; ID Focus; Database. Again, exemplary selections have been made for illustration purposes.
Finally, the user interface 26 includes information about search effort (how long the user is willing to wait). This topic is presented under the label “Search Effort” The user can select by radio button either a rapid ID or a thorough ID. In addition, the user can employ a drop-down list to select what the detected protein threshold or confidence score should be. For illustration purposes here, the interface shows that a thorough ID has been selected and that a detected protein threshold of 2.0 (99.0%) has been chosen. The user can make the desired selections in interface 26 and then click the save, save as, or cancel buttons to save the settings for future use or to abort the process by cancelling The user can select an appropriate name for his or her project which is displayed in the drop-down field 36. In this regard, the save as button would be used when the user wants to create a new name for the workflow or method, which would then appear as one of the choices when the drop-down list 36 is selected. A delete button 38 is also included to allow the user to quickly delete all settings and thus revert to an initialized or blank user interface screen.
In one embodiment of the scientist domain-centric user interface and enabling “soft” translation system a set of business rules can be employed to populate the user interface 26 with its drop-down list and check-box title descriptors and the associated user selectable choices. In one embodiment these business process rules can be expressed using XML files. As will be more fully discussed, these XML files also serve as the instructions by which the translation layer 32 (
As shown in
Some of the user selections can invoke further selections that the workflow engine is able to make automatically by following the hierarchical information expressed in the translations file. For example, see the user choice identified by the name “Special Factors,” which appears as one of the choices under the User Input Translations heading. When the user chooses one of the special factors (also expressed in terminology of the scientific domain) the workflow engine is given a Mod Feature Set value, which the workflow engine can then look up in the Mod Feature Set section of the Translations file. For example, if the user selects “Urea Denaturation” the workflow engine can look up the associated value “Mod Feature Set:12.” This, in turn, allows the workflow engine to jump to the section of the Translations file where Mod Feature Set:12 is described. For convenience, the parameters corresponding to Mod Feature Set:12 are set forth below,
It can be seen from the above example, that a single selection of “Urea Denaturation” by the user can generate a potentially quite complex set of data that the workflow engine can then extract and use to populate the Parameters Template file. Also note in the above example that many of the data values are expressed as probabilities (prob=“0.1”, prob=“0.002”, etc.). The use of probabilistic values (expressing probabilistic rules) allows the workflow engine to populate the Parameters Template file with selected maximum and minimum ranges that, when supplied as parameters to the search algorithm, instruct the algorithm to control the search effort rapidity. Thus, if the user selects “Rapid ID” in the Search Effort portion of the user interface 26, the workflow engine can use these probability values to determine, a priori, what to ask the search algorithm to look for. By appropriate selection of values in the Parameters Template, the search algorithm can be controlled to perform exhaustive searches, or less exhaustive searches where some of the possible search paths are pruned or suppressed as the search proceeds.
By expressing the business logic or business rules in the form of hierarchical XML files, the embodiment illustrated in
From the foregoing, it will be appreciated that the scientific domain-centric user interface and associated “soft” translation system removes much of the complexity and chances for making arbitrary, counterproductive parameter settings. Thus the user is no longer confronted with making arcane decisions about algorithm control parameters, such as mass tolerances, the number of missed cleavages allowed, selection of specific modifications and/or mutations, and subtopics. Instead, the user simply enters information that he or she readily knows, about what the user did in the lab, what the user wants to know from the analysis and how long the user is willing to wait for results (whether high accuracy, long search time is appropriate or whether a lower accuracy, fast answer is acceptable).
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