fig1 to 3 illustrate a system 100 that can enable researchers 106 to use otherwise discarded biological samples 110 a in their studies . such samples can include tissue samples and / or samples of blood or other bodily fluids . as shown in fig1 the system 100 includes a donor institution 104 with a pathology department . often such departments use only a portion of a sample to perform a given medical test . in the past , the remainder was typically discarded despite the difficulty of obtaining such samples for research . as shown in fig1 a repository 102 collects excess samples 111 a from a donor institution 104 for distribution to interested researchers 106 . in addition to physically delivering the samples 110 a to the repository , a donor institution 104 can also transmit information specifying characteristics of a sample that may be of interest to a researcher 106 . for example , as shown , the institution 104 transmits a medical record 112 of a patient providing the sample as well as a pathology report 114 about the sample . the transmission may be performed via interaction with a repository 102 server over a network 108 using a variety of network transfer protocols such as http ( hypertext transfer protocol ) or ftp ( file transfer protocol ). the medical report 112 may include physical data ( e . g ., the patient &# 39 ; s approximate age , weight , gender ) and health data such as different health risks ( e . g ., whether the patient smokes cigarettes ) and / or diagnosed illness ( es ) of the patient . the medical report 112 may also include demographic data . for confidentiality , the medical report 112 may omit the patient &# 39 ; s real name and other personal identifiers . the pathology report 114 includes the results of the donor institution &# 39 ; s 104 analysis of the sample 110 a . for example , the pathology report 114 may include data identifying the sample 110 a as cancerous . the pathology report 114 may also include data about the sample such as where a tissue sample was extracted from and other sample characteristics . as shown in fig1 the donor institution 104 can transmit the reports 112 , 114 over a network 108 , such as the internet , to a repository 102 . the repository 102 can store the received records 116 , 118 associated with the sample 110 a in a database that stores records associated with other samples . as shown in fig2 the repository 102 server can permit researchers 106 to browse an on - line inventory for samples 110 meeting specified criteria . as shown , a researcher 106 can submit a query 120 to the server 102 over the network 108 specifying criteria , for example , of the tissue type , diagnosis , and so forth . for instance , the researcher 106 may interact with a user interface such as the one shown in fig5 or 6 . after identifying samples 110 matching the query 120 , the repository 102 server can transmit a query response 122 back to the researcher 106 . for example , the response 122 may feature a dynamically constructed web - page that includes a list of available tissue samples 110 . such a web - page may include links featuring images of the tissue samples , the “ clinical story ” of the donors , or other information in the pathology or medical reports . as shown in fig3 after receiving a selection 126 of desired tissue samples from the researcher 106 , the repository server 102 can initiate physical delivery 110 b of the sample in a wide variety of researcher specified forms . for example , the researcher 106 can request frozen or formalin fixed gross samples , frozen or paraffin tissue blocks , extracted rna , dna and proteins , tissue microarrays , rna derived from laser capture microdissection , and so forth . the research may also request images of selected samples . while fig1 to 3 show a single donor institution 104 and researcher 106 , the system 100 can provide services to many different institutions 104 and researchers 106 . the diverse needs of users , the variety of concepts embodied by a given sample , and the flexibility of many coding systems can make searching for a sample having particular characteristics more difficult . thus , the system shown in fig1 to 3 can benefit from a scheme that enables users to specify tissue samples of interest with great specificity . [ 0024 ] fig4 illustrates a coding approach that uses snomed - rt ( snomed - reference terminology ) concepts as building blocks for concepts of greater specificity than provided by existing snomed - rt concepts . that is , a finely grained concept can be represented through the pre - coordination of a collection of snomed concept codes . for example , snomed does not currently offer a code for “ metastatic adenocarcinoma of the stomach ”. however , a pre - coordinated code for this concept may be fashioned from the combination of snomed concept codes for “ neoplasm of stomach ” ( 126824007 ), “ adenocarcinoma no subtype ” ( 35917007 ), and “ metastatic ” ( 8707003 ). that is , combining the codes for these concepts ( e . g ., “ 126824007 ^ 35917007 ^ 8707003 ”) yields a pre - coordinated code for the narrow concept of “ metastatic adenocarcinoma of the stomach ”. by defining this concept and its associated pre - coordinated code , researchers can narrowly specify concepts and more precisely code information . this can permit more exact categorization and searching . additionally , preservation of the “ building block ” codes preserves a broad search capability . the approach can also “ normalize ” diagnosis coding across different institutions and researchers . that is , a normalized controlled vocabulary provides explicit , concise , and predictable names across donor institutions and clients , for both data entry and query parameter setting . thus , the approach can ensure that different institutions encode the same diagnosis using the same code . this can also enable researchers to find tissue samples of interest without the guesswork involved in hypothesizing how others may have encoded a diagnosis . in greater detail , fig4 illustrates a collection 130 - 134 of concepts 130 a and their corresponding codes 130 b . while illustrated using snomed concepts and codes , a wide variety of other standard coding schemes may be used . as shown , the different codes in the collection 130 - 134 correspond to different related concepts regarding a diagnosis . in the case of snomed , the collection 130 - 134 of codes may feature codes from different snomed axes ( categories ). as shown , concatenating the collection 130 - 134 of codes together can create a pre - coordinated code 140 a . the pre - coordinated code 140 a corresponds to a textual description of a narrow concept 140 h . appendix a includes a sample database of such codes expressing a wide variety of diagnoses . again , institutions can use these codes to encode their diagnoses of submitted samples . similarly , researchers can use these codes to search for samples of interest . as shown in fig4 the concatenation may feature delimiters separating the different codes ( e . g ., the “^ ” characters ). alternatively , the code 140 a may pad each “ sub - code ” 130 b such that each concept code occupies a predetermined portion of the resulting code 140 a if desired . regardless , the code 140 a retains the information of contributing codes 130 - 134 in the pre - coordinated code 140 a . while straightforward , this technique can provide a number of benefits . again , adopting the technique can permit researchers to identify characteristics with great specificity . the approach can also result in the presentation of a single way to encode a diagnosis associated with a tissue sample . again , this can ease retrieval by researchers . while the resulting code 140 a does not appear in the standard coding scheme of the contributing codes 130 - 134 ( e . g ., the concatenated code does not appear in snomed ), the code 140 a construction preserves the constituent standard code building blocks . this can enable researchers to perform a search for tissue samples based on a standard snomed code as well as the pre - coordinated code 140 a . for example , a researcher can search for all tissue samples that include the snomed code , “ 8707003 ”, for the concept “ metastatic ”. though tissue samples may have been assigned a composite code 140 a of “ 126927001 ^ 35917007 ^ 8707003 ”, the retrieval software can identify all samples featuring the snomed code “ 8707003 ” within their pre - coordinated codes . while fig4 illustrates an example of a pre - coordinated concept formed from three “ sub - concepts ”, different pre - coordinated codes may feature different number of concepts . for example , a concept of “ adenocarcinoma of stomach , signet ring cell type ” may be formed from the concepts “ neoplasm of stomach ” and “ signet ring cell carcinoma ”, represented by codes 126824007 and 87737001 , respectively . the concatenation order of codes and the expression of a concept may be performed in accordance with different syntax rules . for example , a rule may specify an ordering of terms according to their snomed axis ( e . g ., snomed disease or disorder code , morphology code , site or type code , followed by modifying codes ). such a general rule may be qualified . for example , a rule may remove terms ( e . g ., “ invasive ”, “ infiltrative ”, “ residual ”, and “ minimal ”) from a concept name or replace terms ( e . g ., use “ focal ” instead of “ multifocal ” if the latter is specified ) to enhance normalization . a given coding scheme may sometimes fail to offer a useful building block for inclusion in a pre - coordinated code / concept . for example , snomed - rt does not currently provide a concept or code for the presence of the “ brca1 ” gene . thus , the code manager may create local extensions to a given coding standard . for example , a code manager may define a code of “ ca079954 ” to represent the concept of the “ brca1 ” gene , where “ ca ” identifies a code as an extension to the standard coding scheme . while described above as creating a pre - coordinated diagnosis code , the techniques may be used to create other kinds of pre - coordinated codes that may describe a characteristic of a sample . for example , the approach described above can be used to create pre - coordinated tissue codes ( e . g ., codes describing a particular tissue ) or procedure codes ( e . g ., codes describing a particular procedure ). for example , a pre - coordinated code for the tissue concept “ tendon of foot ” may be formed by concatenating 13024001 and 56459004 which correspond to the concepts “ tendons ” and “ foot ”, respectively . a system using the pre - coordinated codes may shield end users from explicitly specifying the codes . for instance , fig5 and 6 illustrate user interfaces that enable a user to specify characteristics of a sample using the pre - coordinated codes . for example , fig5 illustrates a user interface 150 that enables a user to specify a diagnosis by navigating through a series of text description menus 152 - 156 . the menus shown enable the user to select whether or not the diagnosis is neoplastic 152 and the type of tissue sample 154 . based on these narrowing categories , the user interface 150 can present a text menu 156 of specific concepts having pre - coordinated codes . the user interface 150 may also include other “ widgets ”. for example , the interface 150 may enable a researcher to specify a format 158 and / or a tissue appearance 160 . after selecting a diagnosis 156 and specifying other attributes 158 , 160 , a user may submit a corresponding query 162 . such a query may include the actual pre - coordinated code corresponding to a selected concept or may include information used to deduce the code such as the concept text or an integer identifying the code . the query may be included as url parameters or included in a message sent to the repository 102 server . the user interface shown in fig5 may be expressed in instructions for transmission over the internet to a users client ( e . g ., web - browser ). for example , the instructions may feature markup language instructions such as html ( hypertext markup language ), xml ( extensible markup language ), or another sgml ( standard generalized markup language ) language . such instructions may be transmitted via a network protocol such as http ( hypertext transfer protocol ) and / or https ( hypertext transfer protocol secure ). the user interface of fig5 presents the concept text of pre - coordinated codes to guide a user &# 39 ; s selection . however , other implementations may use other user interface techniques . for example , the user interface may present images of tissue samples and user selection of the image to identify a search for like samples . behind the scenes , the system can identify the each image may have one or more associated pre - coordinated codes for use in the query . [ 0039 ] fig7 illustrates operation of a system 170 using the pre - coordinated codes described above . as shown , after generating 172 a pre - coordinated code to represent a concept , the system 170 makes such code available for assignment 174 to a tissue sample , for example , by a donor institution . thereafter , a received 176 query may identify one of the composite codes . based on this query , the system 170 can determine tissue samples meeting the user specified criteria . the techniques described herein are not limited to any particular configuration . for example , the repository 102 may feature an websphere ™ web - server and an oracle database back - end or some other configuration . preferably , the techniques are implemented in computer programs executing on programmable computers that each include a processor , a storage medium readable by the processor ( including volatile and non - volatile memory and / or storage elements ), at least one input device , and one or more output devices . each program is preferably implemented in high level procedural or object oriented programming language to communicate with a computer system . however , the programs can be implemented in assembly or machine language , if desired . in any case the language may be compiled or interpreted language . each such computer program is preferably stored on a storage medium or device ( e . g ., cd - rom , hard disk , or magnetic disk ) that is readable by a general or special purpose programmable computer for configuring and operating the computer when the storage medium or device is read by the computer to perform the procedures described herein . the system may also be considered to be implemented as a computer - readable storage medium , configured with a computer program , where the storage medium so configured causes a computer to operate in a specific and predefined manner .