Systems and methods for detecting biological features

Abstract

A computer having a memory stores instructions for receiving data. The data comprises one or more characteristics for each cellular constituent in a plurality of cellular constituents that have been measured in a test organism of a species or a test biological specimen from an organism of the species. The memory further stores instructions for computing a model in a plurality of models, wherein the model is characterized by a model score that represents the likelihood of a biological feature in the test organism or the test biological specimen. Computation of the model comprises determining the model score using one or more characteristics for one or more cellular constituents in the plurality of cellular constituents. The memory also stores instructions for repeating the instructions for computing one or more times, thereby computing the plurality of models. The memory also stores instructions for communicating computed model scores.

1 . A computer comprising: 
 a central processing unit;    a memory, coupled to the central processing unit, the memory storing: 
 (i) instructions for receiving data, wherein said data comprises one or more characteristics for each cellular constituent in a plurality of cellular constituents that have been measured in a test organism of a species or a test biological specimen from an organism of said species;  
 (ii) instructions for computing a model in a plurality of models, wherein said model is characterized by a model score that represents the likelihood of a biological feature in the test organism or the test biological specimen and wherein said computing said model comprises determining said model score using one or more characteristics for one or more cellular constituents in said plurality of cellular constituents;  
 (iii) instructions for repeating said instructions for computing one or more times, thereby computing said plurality of models; and  
 (iv) instructions for communicating each said model score computed in an instance of said instructions for computing.  
   
     
     
         2 . The computer of  claim 1 , wherein 
 two or more model scores are communicated by said instructions for communicating and wherein each model score in said two or more model scores corresponds to a different model in said plurality of models.    
     
     
         3 . The computer of  claim 1 , wherein 
 five or more model scores are communicated by said instructions for communicating and wherein each model score in said five or more model scores corresponds to a different model in said plurality of models.    
     
     
         4 . The computer of  claim 1  wherein said instructions for receiving data comprise instructions for receiving said data from a remote computer over a wide area network.  
     
     
         5 . The computer of  claim 4  wherein said wide area network is the Internet.  
     
     
         6 . The computer of  claim 1  wherein said instructions for communicating comprise instructions for transmitting each said model score to a remote computer over a wide area network.  
     
     
         7 . The computer of  claim 6  wherein said wide area network is the Internet.  
     
     
         8 . The computer of  claim 1  wherein 
 the test organism or the test biological specimen is deemed to have the biological feature represented by a model in the plurality of models when the model score is in a first range of values; and    the test organism or the test biological specimen is deemed not to have the biological feature represented by the model when the model score is in a second range of values.    
     
     
         9 . The computer of  claim 1  wherein said biological feature is a disease.  
     
     
         10 . The computer of  claim 9  wherein said disease is cancer.  
     
     
         11 . The computer of  claim 9  wherein said disease is breast cancer, lung cancer, prostate cancer, colorectal cancer, ovarian cancer, bladder cancer, gastric cancer, or rectal cancer.  
     
     
         12 . The computer of  claim 1  wherein 
 the plurality of models comprises a first model characterized by a first model score and a second model characterized by a second model score; and    an identity of a cellular constituent whose one or more characteristics is used to compute said first model score is different than an identity of a cellular constituent whose one or more characteristics is used to compute said second model score.    
     
     
         13 . The computer of  claim 1  wherein a characteristic in said one or more characteristics for one or more cellular constituents used to determine the model score for a model in said plurality of models comprises an abundance of said one or more cellular constituents in said test organism of said species or said test biological specimen from an organism of said species.  
     
     
         14 . The computer of  claim 1  wherein the species is human.  
     
     
         15 . The computer of  claim 1  wherein the test biological specimen is a biopsy or other form of sample from a tumor, blood, bone, a breast, a lung, a prostate, a colorectum, an ovary, a bladder, a stomach, or a rectum.  
     
     
         16 . The computer of  claim 1  wherein said one or more characteristics comprises cellular constituent abundance and said data comprises cellular constituent abundances of at least one hundred cellular constituents in said test organism of said species or said test biological specimen from said organism of said species.  
     
     
         17 . The computer of  claim 1  wherein said one or more characteristics comprises cellular constituent abundance and said data comprises cellular constituent abundances of at least five hundred cellular constituents in said test organism of said species or said test biological specimen from said organism of said species.  
     
     
         18 . The computer of  claim 1  wherein said one or more characteristics comprises cellular constituent abundance and said data comprises cellular constituent abundances of at least five thousand cellular constituents in said test organism of said species or said test biological specimen from said organism of said species.  
     
     
         19 . The computer of  claim 1  wherein said one or more characteristics comprises cellular constituent abundance and said data comprises cellular constituent abundances of between one thousand and twenty thousand cellular constituents in said test organism of said species or said test biological specimen from said organism of said species.  
     
     
         20 . The computer of  claim 1  wherein a cellular constituent in said plurality of cellular constituents is mRNA, cRNA or cDNA.  
     
     
         21 . The computer of  claim 1  wherein a cellular constituent in said one or more cellular constituents is a nucleic acid or a ribonucleic acid and a characteristic in said one or more characteristics of said cellular constituent is obtained by measuring a transcriptional state of all or a portion of said cellular constituent in said test organism or said test biological specimen.  
     
     
         22 . The computer of  claim 1  wherein a cellular constituent in said one or more cellular constituents is a protein and a characteristic in said one or more characteristics of said cellular constituent is obtained by measuring a translational state of said cellular constituent in said test organism or said test biological specimen.  
     
     
         23 . The computer of  claim 1  wherein a characteristic in the one or more characteristics of a cellular constituent in the plurality of cellular constituents is determined using isotope-coded affinity tagging followed by tandem mass spectrometry analysis of the cellular constituent using a sample obtained from the test organism or the test biological specimen.  
     
     
         24 . The computer of  claim 1  wherein a characteristic in the one or more characteristics of a cellular constituent in the plurality of cellular constituents is determined by measuring an activity or a post-translational modification of the cellular constituent in a sample obtained from the test organism or in the test biological specimen.  
     
     
         25 . The computer of  claim 1  wherein said biological feature is sensitivity to a drug.  
     
     
         26 . The computer of  claim 1  wherein the plurality of models for which model scores are computed by instances of said instructions for computing collectively represent the likelihood of each of two or more biological features.  
     
     
         27 . The computer of  claim 26  wherein each biological feature in said two or more biological features is a cancer origin.  
     
     
         28 . The computer of  claim 26  wherein said two or more biological features comprises a first disease and a second disease.  
     
     
         29 . The computer of  claim 1  wherein the plurality of models for which model scores are computed by instances of said instructions for computing collectively represent the likelihood of each of five or more biological features.  
     
     
         30 . The computer of  claim 29  wherein each biological feature in said five or more biological features is a cancer origin.  
     
     
         31 . The computer of  claim 29  wherein said five or more biological features comprises a first disease and a second disease.  
     
     
         32 . The computer of  claim 1  wherein the plurality of models for which model scores are computed by instances of said instructions for computing collectively represent the independent likelihood of between two and twenty biological features.  
     
     
         33 . The computer of  claim 32  wherein each biological feature in said between two and twenty biological features is a cancer origin.  
     
     
         34 . The computer of  claim 32  wherein said between two and twenty biological features comprises a first disease and a second disease.  
     
     
         35 . A computer comprising: 
 a central processing unit;    a memory, coupled to the central processing unit, the memory storing: 
 (i) instructions for receiving data, wherein said data comprises one or more characteristics for each cellular constituent in a plurality of cellular constituents that have been measured in a test organism of a species or a test biological specimen from an organism of said species;  
 (ii) instructions for computing a plurality of models, wherein each model in said plurality of models is characterized by a model score that represents the likelihood of a biological feature in the test organism or the test biological specimen and computation of a respective model in said plurality of models comprises determining the model score associated with the respective model using one or more characteristics for one or more cellular constituents in said plurality of cellular constituents; and  
 (iii) instructions for communicating each said model score computed by said instructions for computing.  
   
     
     
         36 . A computer program product for use in conjunction with a computer system, the computer program product comprising a computer readable storage medium and a computer program mechanism embedded therein, the computer program mechanism comprising: 
 (i) instructions for receiving data, wherein said data comprises one or more characteristics for each cellular constituent in a plurality of cellular constituents that have been measured in a test organism of a species or a test biological specimen from an organism of said species;    (ii) instructions for computing a model in a plurality of models, wherein said model is characterized by a model score that represents the likelihood of a biological feature in the test organism or the test biological specimen and said computing said model comprises determining said model score using one or more characteristics for one or more cellular constituents in said plurality of cellular constituents;    (iii) instructions for repeating said instructions for computing one or more times, thereby computing said plurality of models; and    (iv) instructions for communicating each said model score computed in an instance of said instructions for computing.    
     
     
         37 . The computer program product of  claim 36 , wherein 
 two or more model scores are communicated by said instructions for communicating and wherein each model score in said two or more model scores corresponds to a different model in said plurality of models.    
     
     
         38 . The computer program product of  claim 36 , wherein 
 five or more model scores are communicated by said instructions for communicating and wherein each model score in said five or more model scores corresponds to a different model in said plurality of models.    
     
     
         39 . The computer program product of  claim 36  wherein 
 the test organism or the test biological specimen is deemed to have the biological feature represented by a model in the plurality of models when the model score is in a first range of values; and    the test organism or the test biological specimen is deemed not to have the biological feature represented by the model when the model score is in a second range of values.    
     
     
         40 . The computer program product of  claim 36  wherein said biological feature is a disease.  
     
     
         41 . The computer program product of  claim 40  wherein said disease is cancer.  
     
     
         42 . The computer program product of  claim 40  wherein said disease is breast cancer, lung cancer, prostate cancer, colorectal cancer, ovarian cancer, bladder cancer, gastric cancer, or rectal cancer.  
     
     
         43 . The computer program product of  claim 36  wherein 
 the plurality of models comprises a first model characterized by a first model score and a second model characterized by a second model score; and    an identity of a cellular constituent whose one or more characteristics is used to compute said first model score is different than an identity of a cellular constituent whose one or more characteristics is used to compute said second model score.    
     
     
         44 . The computer program product of  claim 36  wherein a characteristic in said one or more characteristics for one or more cellular constituents used to determine the model score for a model in said plurality of models comprises an abundance of said one or more cellular constituents in said test organism of said species or said test biological specimen from an organism of said species.  
     
     
         45 . The computer program product of  claim 36  wherein the species is human.  
     
     
         46 . The computer program product of  claim 36  wherein the test biological specimen is a biopsy or other form of sample from a tumor, blood, bone, a breast, a lung, a prostate, a colorectum, an ovary, a bladder, a stomach, or a rectum.  
     
     
         47 . The computer program product of  claim 36  wherein said one or more characteristics comprises cellular constituent abundance and said data comprises cellular constituent abundances of at least one hundred cellular constituents in said test organism of said species or said test biological specimen from said organism of said species.  
     
     
         48 . The computer program product of  claim 36  wherein said one or more characteristics comprises cellular constituent abundance and said data comprises cellular constituent abundances of at least five hundred cellular constituents in said test organism of said species or said test biological specimen from said organism of said species.  
     
     
         49 . The computer program product of  claim 36  wherein said one or more characteristics comprises cellular constituent abundance and said data comprises cellular constituent abundances of at least five thousand cellular constituents in said test organism of said species or said test biological specimen from said organism of said species.  
     
     
         50 . The computer program product of  claim 36  wherein said one or more characteristics comprises cellular constituent abundance and said data comprises cellular constituent abundances of between one thousand and twenty thousand cellular constituents in said test organism of said species or said test biological specimen from said organism of said species.  
     
     
         51 . The computer program product of  claim 36  wherein a cellular constituent in said plurality of cellular constituents is mRNA, cRNA or cDNA.  
     
     
         52 . The computer program product of  claim 36  wherein a cellular constituent in said one or more cellular constituents is a nucleic acid or a ribonucleic acid and a characteristic in said one or more characteristics of said cellular constituent is obtained by measuring a transcriptional state of all or a portion of said cellular constituent in said test organism or said test biological specimen.  
     
     
         53 . The computer program product  claim 36  wherein a cellular constituent in said one or more cellular constituents is a protein and a characteristic in said one or more characteristics of said cellular constituent is obtained by measuring a translational state of said cellular constituent in said test organism or said test biological specimen.  
     
     
         54 . The computer program product of  claim 36  wherein a characteristic in the one or more characteristics of a cellular constituent in the plurality of cellular constituents is determined using isotope-coded affinity tagging followed by tandem mass spectrometry analysis of the cellular constituent using a sample obtained from the test organism or the test biological specimen.  
     
     
         55 . The computer program product of  claim 36  wherein a characteristic in the one or more characteristics of a cellular constituent in the plurality of cellular constituents is determined by measuring an activity or a post-translational modification of the cellular constituent in a sample obtained from the test organism or in the test biological specimen.  
     
     
         56 . The computer program product of  claim 36  wherein said biological feature is sensitivity to a drug.  
     
     
         57 . A computer program product for use in conjunction with a computer system, the computer program product comprising a computer readable storage medium and a computer program mechanism embedded therein, the computer program mechanism comprising: 
 (i) instructions for receiving data, wherein said data comprises one or more characteristics for each cellular constituent in a plurality of cellular constituents that have been measured in a test organism of a species or a test biological specimen from an organism of said species;    (ii) instructions for computing a plurality of models, wherein each model in said plurality of models is characterized by a model score that represents the likelihood of a biological feature in the test organism or the test biological specimen and computation of a respective model in said plurality of models comprises determining the model score associated with the respective model using one or more characteristics for one or more cellular constituents in said plurality of cellular constituents; and    (iii) instructions for communicating each said model score computed in an instance of said instructions for computing.    
     
     
         58 . A method, comprising: 
 receiving data, wherein said data comprises one or more characteristics for each cellular constituent in a plurality of cellular constituents that have been measured in a test organism of a species or a test biological specimen from an organism of said species;    computing a model in a plurality of models, wherein said model is characterized by a model score that represents the likelihood of a biological feature in the test organism or the test biological specimen and wherein said computing said model comprises determining said model score using one or more characteristics for one or more cellular constituents in said plurality of cellular constituents;    repeating said computing one or more times thereby computing said plurality of models; and    communicating each said model score computed in an instance of said computing.    
     
     
         59 . The method of  claim 58 , wherein two or more model scores are communicated by said communicating step and wherein each model score in said two or more model scores corresponds to a different model in said plurality of models.  
     
     
         60 . The method of  claim 58 , wherein five or more model scores are communicated by said instructions for communicating and wherein each model score in said two or more model scores corresponds to a different model in said plurality of models.  
     
     
         61 . The method of  claim 58  wherein 
 the test organism or the test biological specimen is deemed to have the biological feature represented by a model in the plurality of models when the model score is in a first range of values; and    the test organism or the test biological specimen is deemed not to have the biological feature represented by the model when the model score is in a second range of values.    
     
     
         62 . The method of  claim 58  wherein said biological feature is a disease.  
     
     
         63 . The method of  claim 62  wherein said disease is cancer.  
     
     
         64 . The method of  claim 62  wherein said disease is breast cancer, lung cancer, prostate cancer, colorectal cancer, ovarian cancer, bladder cancer, gastric cancer, or rectal cancer.  
     
     
         65 . The method of  claim 58  wherein 
 the plurality of models comprises a first model characterized by a first model score and a second model characterized by a second model score; and    an identity of a cellular constituent whose one or more characteristics is used to compute said first model score is different than an identity of a cellular constituent whose one or more characteristics is used to compute said second model score.    
     
     
         66 . The method of  claim 58  wherein a characteristic in said one or more characteristics for one or more cellular constituents used to determine the model score for a model in said plurality of models comprises an abundance of said one or more cellular constituents in said test organism of said species or said test biological specimen from an organism of said species.  
     
     
         67 . The method of  claim 58  wherein the species is human.  
     
     
         68 . The method of  claim 58  wherein the test biological specimen is a biopsy or other form of sample from a tumor, blood, bone, a breast, a lung, a prostate, a colorectum, an ovary, a bladder, a stomach, or a rectum.  
     
     
         69 . The method of  claim 58  wherein said one or more characteristics comprises cellular constituent abundance and said data comprises cellular constituent abundances of at least one hundred cellular constituents in said test organism of said species or said test biological specimen from said organism of said species.  
     
     
         70 . The method of  claim 58  wherein said one or more characteristics comprises cellular constituent abundance and said data comprises cellular constituent abundances of at least five hundred cellular constituents in said test organism of said species or said test biological specimen from said organism of said species.  
     
     
         71 . The method of  claim 58  wherein said one or more characteristics comprises cellular constituent abundance and said data comprises cellular constituent abundances of at least five thousand cellular constituents in said test organism of said species or said test biological specimen from said organism of said species.  
     
     
         72 . The method of  claim 58  wherein said one or more characteristics comprises cellular constituent abundance and said data comprises cellular constituent abundances of between one thousand and twenty thousand cellular constituents in said test organism of said species or said test biological specimen from said organism of said species.  
     
     
         73 . The method of  claim 58  wherein a cellular constituent in said plurality of cellular constituents is mRNA, cRNA or cDNA.  
     
     
         74 . The method of  claim 58  wherein a cellular constituent in said one or more cellular constituents is a nucleic acid or a ribonucleic acid and a characteristic in said one or more characteristics of said cellular constituent is obtained by measuring a transcriptional state of all or a portion of said cellular constituent in said test organism or said test biological specimen.  
     
     
         75 . The method of  claim 58  wherein a cellular constituent in said one or more cellular constituents is a protein and a characteristic in said one or more characteristics of said cellular constituent is obtained by measuring a translational state of said cellular constituent in said test organism or said test biological specimen.  
     
     
         76 . The method of  claim 58  wherein a characteristic in the one or more characteristics of a cellular constituent in the plurality of cellular constituents is determined using isotope-coded affinity tagging followed by tandem mass spectrometry analysis of the cellular constituent using a sample obtained from the test organism or the test biological specimen.  
     
     
         77 . The method of  claim 58  wherein a characteristic in the one or more characteristics of a cellular constituent in the plurality of cellular constituents is determined by measuring an activity or a post-translational modification of the cellular constituent in a sample obtained from the test organism or in the test biological specimen.  
     
     
         78 . The method of  claim 58  wherein said biological feature is sensitivity to a drug.  
     
     
         79 . The method of  claim 58  wherein the plurality of models for which model scores are computed by instances of said computing collectively represent the likelihood of each of two or more biological features.  
     
     
         80 . The method of  claim 79  wherein each biological feature in said two or more biological features is a cancer origin.  
     
     
         81 . The method of  claim 79  wherein said two or more biological features comprises a first disease and a second disease.  
     
     
         82 . The method of  claim 58  wherein the plurality of models for which model scores are computed by instances of said computing collectively represent the likelihood of each of five or more biological features.  
     
     
         83 . The method of  claim 82  wherein each biological feature in said five or more biological features is a cancer origin.  
     
     
         84 . The method of  claim 82  wherein said five or more biological features comprises a first disease and a second disease.  
     
     
         85 . The method of  claim 58  wherein the plurality of models for which model scores are computed by instances of said computing collectively represent the independent likelihood of between two and twenty biological features.  
     
     
         86 . The method of  claim 85  wherein each biological feature in said between two and twenty biological features is a cancer origin.  
     
     
         87 . The method of  claim 85  wherein said between two and twenty biological features comprises a first disease and a second disease  
     
     
         88 . A method comprising: 
 receiving data, wherein said data comprises one or more characteristics for each cellular constituent in a plurality of cellular constituents that have been measured in a test organism of a species or a test biological specimen from an organism of said species;    computing a plurality of models, wherein each model in said plurality of models is characterized by a model score that represents the likelihood of a biological feature in the test organism or the test biological specimen and computation of a respective model in said plurality of models comprises determining the model score associated with the respective model using one or more characteristics for one or more cellular constituents in said plurality of cellular constituents; and    communicating each said model score computed in an instance of said computing.    
     
     
         89 . A computer comprising: 
 a central processing unit;    a memory, coupled to the central processing unit, the memory storing: 
 (i) instructions for sending data, wherein said data comprises one or more characteristics for each cellular constituent in a plurality of cellular constituents that have been measured in a test organism of a species or a test biological specimen from an organism of said species; and  
 (ii) instructions for receiving a plurality of model scores, wherein each model score corresponds to a model in a plurality of models and wherein each model in said plurality of models is characterized by a model score that represents the likelihood of a biological feature in the test organism or the test biological specimen and said computing said model comprises determining said model score using one or more characteristics for one or more cellular constituents in said plurality of cellular constituents.  
   
     
     
         90 . The computer of  claim 89 , wherein said plurality of model scores consists of two or more model scores and wherein each model score in said two or more model scores corresponds to a different model in said plurality of models.  
     
     
         91 . The computer of  claim 89 , wherein said plurality of model scores consists of five or more model scores are communicated by said instructions for communicating and wherein each model score in said five or more model scores corresponds to a different model in said plurality of models.  
     
     
         92 . The computer of  claim 89  wherein said instructions for sending data comprise instructions for sending said data from said remote computer to a remove computer over a wide area network.  
     
     
         93 . The computer of  claim 92  wherein said wide area network is the Internet.  
     
     
         94 . The computer of  claim 89  wherein said instructions for receiving comprise instructions for receiving said plurality of model scores from a remote computer over a wide area network.  
     
     
         95 . The computer of  claim 94  wherein said wide area network is the Internet.  
     
     
         96 . The computer of  claim 89  wherein 
 the test organism or the test biological specimen is deemed to have the biological feature represented by a model in the plurality of models when the model score is in a first range of values; and    the test organism or the test biological specimen is deemed not to have the biological feature represented by the model when the model score is in a second range of values.    
     
     
         97 . The computer of  claim 89  wherein said biological feature is a disease.  
     
     
         98 . The computer of  claim 97  wherein said disease is cancer.  
     
     
         99 . The computer of  claim 97  wherein said disease is breast cancer, lung cancer, prostate cancer, colorectal cancer, ovarian cancer, bladder cancer, gastric cancer, or rectal cancer.  
     
     
         100 . The computer of  claim 89  wherein 
 the plurality of models comprises a first model characterized by a first model score and a second model characterized by a second model score; and    an identity of a cellular constituent whose one or more characteristics is used to compute said first model score is different than an identity of a cellular constituent whose one or more characteristics is used to compute said second model score.    
     
     
         101 . The computer of  claim 89  wherein a characteristic in said one or more characteristics for one or more cellular constituents used to determine the model score for a model in said plurality of models comprises an abundance of said one or more cellular constituents in said test organism of said species or said test biological specimen from an organism of said species.  
     
     
         102 . The computer of  claim 89  wherein the species is human.  
     
     
         103 . The computer of  claim 89  wherein the test biological specimen is a biopsy or other form of sample from a tumor, blood, bone, a breast, a lung, a prostate, a colorectum, an ovary, a bladder, a stomach, or a rectum.  
     
     
         104 . The computer of  claim 89  wherein said one or more characteristics comprises cellular constituent abundance and said data comprises cellular constituent abundances of at least one hundred cellular constituents in said test organism of said species or said test biological specimen from said organism of said species.  
     
     
         105 . The computer of  claim 89  wherein said one or more characteristics comprises cellular constituent abundance and said data comprises cellular constituent abundances of at least five hundred cellular constituents in said test organism of said species or said test biological specimen from said organism of said species.  
     
     
         106 . The computer of  claim 89  wherein said one or more characteristics comprises cellular constituent abundance and said data comprises cellular constituent abundances of at least five thousand cellular constituents in said test organism of said species or said test biological specimen from said organism of said species.  
     
     
         107 . The computer of  claim 89  wherein said one or more characteristics comprises cellular constituent abundance and said data comprises cellular constituent abundances of between one thousand and twenty thousand cellular constituents in said test organism of said species or said test biological specimen from said organism of said species.  
     
     
         108 . The computer of  claim 89  wherein a cellular constituent in said plurality of cellular constituents is mRNA, cRNA or cDNA.  
     
     
         109 . The computer of  claim 89  wherein a cellular constituent in said one or more cellular constituents is a nucleic acid or a ribonucleic acid and a characteristic in said one or more characteristics of said cellular constituent is obtained by measuring a transcriptional state of all or a portion of said cellular constituent in said test organism or said test biological specimen.  
     
     
         110 . The computer of  claim 89  wherein a cellular constituent in said one or more cellular constituents is a protein and a characteristic in said one or more characteristics of said cellular constituent is obtained by measuring a translational state of said cellular constituent in said test organism or said test biological specimen.  
     
     
         111 . The computer of  claim 89  wherein a characteristic in the one or more characteristics of a cellular constituent in the plurality of cellular constituents is determined using isotope-coded affinity tagging followed by tandem mass spectrometry analysis of the cellular constituent using a sample obtained from the test organism or the test biological specimen.  
     
     
         112 . The computer of  claim 89  wherein a characteristic in the one or more characteristics of a cellular constituent in the plurality of cellular constituents is determined by measuring an activity or a post-translational modification of the cellular constituent in a sample obtained from the test organism or in the test biological specimen.  
     
     
         113 . The computer of  claim 89  wherein said biological feature is sensitivity to a drug.  
     
     
         114 . The computer of  claim 89  wherein the plurality of models collectively represent the likelihood of each of two or more biological features.  
     
     
         115 . The computer of  claim 114  wherein each biological feature in said two or more biological features is a cancer origin.  
     
     
         116 . The computer of  claim 114  wherein said two or more biological features comprises a first disease and a second disease.  
     
     
         117 . The computer of  claim 89  wherein the plurality of models collectively represent the likelihood of each of five or more biological features.  
     
     
         118 . The computer of  claim 117  wherein each biological feature in said five or more biological features is a cancer origin.  
     
     
         119 . The computer of  claim 117  wherein said five or more biological features comprises a first disease and a second disease.  
     
     
         120 . The computer of  claim 89  wherein the plurality of models for which model scores are computed by instances of said instructions for computing collectively represent the independent likelihood of between two and twenty biological features.  
     
     
         121 . The computer of  claim 120  wherein each biological feature in said between two and twenty biological features is a cancer origin.  
     
     
         122 . The computer of  claim 120  wherein said between two and twenty biological features comprises a first disease and a second disease.  
     
     
         123 . A computer program product for use in conjunction with a computer system, the computer program product comprising a computer readable storage medium and a computer program mechanism embedded therein, the computer program mechanism comprising: 
 (i) instructions for sending data, wherein said data comprises one or more characteristics for each cellular constituent in a plurality of cellular constituents that have been measured in a test organism of a species or a test biological specimen from an organism of said species; and    (ii) instructions for receiving a plurality of model scores, wherein each model score corresponds to a model in a plurality of models and wherein each model in said plurality of models is characterized by a model score that represents the likelihood of a biological feature in the test organism or the test biological specimen and said computing said model comprises determining said model score using one or more characteristics for one or more cellular constituents in said plurality of cellular constituents.    
     
     
         124 . A method comprising: 
 (i) sending data, wherein said data comprises one or more characteristics for each cellular constituent in a plurality of cellular constituents that have been measured in a test organism of a species or a test biological specimen from an organism of said species; and    (ii) receiving a plurality of model scores, wherein each model score corresponds to a model in a plurality of models and wherein each model in said plurality of models is characterized by a model score that represents the likelihood of a biological feature in the test organism or the test biological specimen and said computing said model comprises determining said model score using one or more characteristics for one or more cellular constituents in said plurality of cellular constituents.    
     
     
         125 . The method of  claim 58  wherein said biological feature comprises sensitivity or resistance to a therapy.  
     
     
         126 . The method of  claim 125  wherein said therapy is an administration of a drug.  
     
     
         127 . The method of  claim 58  wherein said biological feature comprises sensitivity or resistance to a therapy combination.  
     
     
         128 . The method of  claim 127  wherein said therapy combination is an administration of a combination of drugs.  
     
     
         129 . The method of  claim 58  wherein said biological feature comprises a metastatic potential of a disease likelihood or recurrence.  
     
     
         130 . A computer comprising: 
 a central processing unit;    a memory, coupled to the central processing unit, the memory storing: 
 (i) instructions for receiving data, wherein said data comprises one or more aspects of the biological state of each cellular constituent in a plurality of cellular constituents that have been measured in a test organism of a species or a test biological specimen from an organism of said species;  
 (ii) instructions for computing a model in a plurality of models, wherein said computing produces a model characterization for the model that indicates whether said test organism of said species or said test biological specimen from said organism of said species is a member of a biological sample class and wherein said computing said model comprises characterizing said model using one or more aspects of the biological state of one or more cellular constituents in said plurality of cellular constituents;  
 (iii) instructions for repeating said instructions for computing one or more times, thereby computing said plurality of models; and  
 (iv) instructions for communicating each said model characterization computed in an instance of said instructions for computing.  
   
     
     
         131 . The computer of  claim 130  wherein said instructions for receiving data comprise instructions for receiving said data from a remote computer over a wide area network.  
     
     
         132 . The computer of  claim 131  wherein said wide area network is the Internet.  
     
     
         133 . The computer of  claim 130  wherein said biological sample class is a disease.  
     
     
         134 . The computer of  claim 133  wherein said disease is cancer.  
     
     
         135 . A computer comprising: 
 a central processing unit;    a memory, coupled to the central processing unit, the memory storing: 
 (i) instructions for receiving data, wherein said data comprises one or more aspects of the biological state of each cellular constituent in a plurality of cellular constituents that have been measured in a test organism of a species or a test biological specimen from an organism of said species;  
 (ii) instructions for computing a plurality of models, wherein said computing produces a model characterization for each model in said plurality of models that indicates whether said test organism of said species or said test biological specimen from said organism of said species is a member of a biological sample class and wherein said computing comprises characterizing each said model in said plurality of models using one or more aspects of the biological state of one or more cellular constituents in said plurality of cellular constituents; and  
 (iii) instructions for communicating each said model characterization computed by said instructions for computing.  
   
     
     
         136 . A computer program product for use in conjunction with a computer system, the computer program product comprising a computer readable storage medium and a computer program mechanism embedded therein, the computer program mechanism comprising: 
 (i) instructions for receiving data, wherein said data comprises one or more aspects of the biological state of each cellular constituent in a plurality of cellular constituents that have been measured in a test organism of a species or a test biological specimen from an organism of said species;    (ii) instructions for computing a model in a plurality of models, wherein said computing produces a model characterization for the model that indicates whether said test organism of said species or said test biological specimen from said organism of said species is a member of a biological sample class and wherein said computing said model comprises characterizing said model using one or more aspects of the biological state of one or more cellular constituents in said plurality of cellular constituents;    (iii) instructions for repeating said instructions for computing one or more times, thereby computing said plurality of models; and    (iv) instructions for communicating each said model characterization computed in an instance of said instructions for computing.    
     
     
         137 . A computer program product for use in conjunction with a computer system, the computer program product comprising a computer readable storage medium and a computer program mechanism embedded therein, the computer program mechanism comprising: 
 (i) instructions for receiving data, wherein said data comprises one or more aspects of the biological state of each cellular constituent in a plurality of cellular constituents that have been measured in a test organism of a species or a test biological specimen from an organism of said species;    (ii) instructions for computing a plurality of models, wherein said computing produces a model characterization for each model in said plurality of models that indicates whether said test organism of said species or said test biological specimen from said organism of said species is a member of a biological sample class and wherein said computing comprises characterizing each said model in said plurality of models using one or more aspects of the biological state of one or more cellular constituents in said plurality of cellular constituents; and    (iii) instructions for communicating each said model characterization computed by said instructions for computing.    
     
     
         138 . A method, comprising: 
 receiving data, wherein said data comprises one or more aspects of the biological state of each cellular constituent in a plurality of cellular constituents that have been measured in a test organism of a species or a test biological specimen from an organism of said species;    computing a model in a plurality of models, wherein said computing produces a model characterization for the model that indicates whether said test organism of said species or said test biological specimen from said organism of said species is a member of a biological sample class and wherein said computing said model comprises characterizing said model using one or more aspects of the biological state of one or more cellular constituents in said plurality of cellular constituents;    repeating said computing one or more times thereby computing said plurality of models; and    communicating each said model characterization computed in an instance of said computing.    
     
     
         139 . A method comprising: 
 receiving data, wherein said data comprises one or more aspects of the biological state of each cellular constituent in a plurality of cellular constituents that have been measured in a test organism of a species or a test biological specimen from an organism of said species;    computing a plurality of models, wherein said computing produces a model characterization for each model in said plurality of models that indicates whether said test organism of said species or said test biological specimen from said organism of said species is a member of a biological sample class and wherein said computing comprises characterizing each said model in said plurality of models using one or more aspects of the biological state of one or more cellular constituents in said plurality of cellular constituents; and    communicating each said model characterization computed.