1. A method of rendering an application view and connecting a component’s behavior to events on the user interface, the method comprising;
registering a view object as a listener on a document in data model that correspond to events on the computer display;
instantiating and associating an object that contains the computational logic of a component with the view object; and
identifying the appropriate references related to the component in the data model that correspond to events on the user interface and registering the components events.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A method of determining an initial concentration (Q0) of a target nucleic acid template in a sample, the method comprising the steps of:
a) amplifying said target nucleic acid template and a plurality of standard templates, each of said standard templates present at a different, known copy number, in a nucleic acid amplification reaction regimen comprising a plurality of cycles of primer annealing, primer elongation and strand dissociation, wherein said reaction is performed using a reaction mixture comprising said target nucleic acid template and said plurality of standard templates, and wherein the efficiency of amplification, E, is similar for said plurality of standards and said target template;
b) measuring, at plural cycles of said amplifying regimen, fluorescent signals from said target and each of said plurality of standard templates after nucleic acid species in an aliquot taken from the reaction mixture are separated by capillary electrophoresis, wherein said measuring generates a set of measurements for each said template;
c) estimating a cycle threshold (Ct) value for each of said plurality of standard templates and said target template, wherein the Ct value is estimated by a method comprising the steps, for each set of measurements for each said template, of:
i) compiling a candidate list of all sets of consecutive signal measurements with cardinality 3 or greater;
ii) removing those signal measurements from said candidate list for which peak area measurement is less than peak area measurement at the previous cycle;
iii) computing a best-fitting line by linear regression for each set of measurements, said line representing a log-linear amplification curve described by equation (1):
log(measured value)=C0+EC
wherein C is the cycle number, C0 is the X intercept and E is the slope of the line;
iv) computing a fitness score for each of said target nucleic acid and said plurality of standards, wherein the fitness score is computed as a weighted sum of the correlation coefficient of the linear regression computed in step (iii), the cardinality of the candidate data set, and proximity to the fluorescence threshold;
v) selecting the set with the highest fitness score as the best set for each of said target nucleic acid and said plurality of standards; and
vi) computing Ct from the best set from each of said target nucleic acid and said plurality of standards, wherein Ct is computed by:
A) choosing a threshold value for log(measured value) of equation (1)
B) solving equation (1) for C when log(measured value) equals the chosen threshold value, C0 equals the X intercept determined in step (c)(iii) and E equals the slope determined in step (c)(iii);
C) setting Ct equal to the solved value of C;
d) generating a standard curve by plotting Ct values estimated in step (c) on the y axis for each of said plurality of said standard templates versus the log of said known copy number on the x axis for each said standard template; and
e) calculating an initial concentration (Q0) for said target nucleic acid template by solving the equation
C
t
\u2061
(
target
)
=
I
–
log
\u2061
(
Q
0
)
log
\u2061
(
E
R
)
for Q0, wherein I is the X intercept of said standard curve and ER is the efficiency obtained from said standard curve.
2. The method of claim 1 wherein said measurements of step (b) are entered into a computer-readable physical memory, and wherein steps (c)-(e) are performed by a computer processor executing instructions, encoded on a computer-readable physical memory, for performing such steps.
3. The method of claim 1 wherein each of said standard templates and said target nucleic acid are amplified by the same pair of oligonucleotide primers.
4. The method of claim 1 wherein said measuring step (b) is performed on a plurality of aliquots taken from said reaction mixture at respective plural cycles during said amplifying regimen.
5. A non-transitory computer-readable physical storage medium comprising instructions, that when executed by a processor, cause the processor to perform a procedure comprising the steps of:
a) receiving a plurality of measurements obtained from a plurality of standard templates;
b) receiving a plurality of measurements obtained from a target template;
c) estimating a cycle threshold (CO value for each of said plurality of standard templates and said target template, wherein the Ct value is estimated by a method comprising the steps, for each set of measurements for each said template, of:
i) compiling a candidate list of all sets of consecutive signal measurements with cardinality 3 or greater;
ii) removing those signal measurements from said candidate list for which peak area measurement is less than peak area measurement at the previous cycle;
iii) computing a best-fitting line by linear regression for each set of measurements, said line representing a log-linear amplification curve described by equation (1):
log(measured value)=C0+EC
wherein C is the cycle number, C0 is the X intercept and E is the slope of the line;
iv) computing a fitness score for each of said target nucleic acid and said plurality of standards, wherein the fitness score is computed as a weighted sum of the correlation coefficient of the regression computed in step (iii), the cardinality of the candidate data set, and proximity to the fluorescence threshold;
v) selecting the set with the highest fitness score as the best set for each of said target nucleic acid and said plurality of standards; and
vi) computing Ct from the best set from each of said target nucleic acid and said plurality of standards, wherein Ct is computed by:
A) choosing a threshold value for log(measured value) of equation (1)
B) solving equation (1) for C when log(measured value) equals the chosen threshold value, C0 equals the X intercept determined in step (c)(iii) and E equals the slope determined in step (c)(iii);
C) setting Ct equal to the solved value of C;
d) generating a standard curve by plotting Ct values estimated in step (c) on the y axis for each of said plurality of said standard templates versus the log of said known copy number on the x axis for each said standard template; and
e) calculating an initial concentration (Q0) for said target nucleic acid template by solving the equation
C
t
\u2061
(
target
)
=
I
–
log
\u2061
(
Q
0
)
log
\u2061
(
E
R
)
for Q0, wherein I is the X intercept of said standard curve and ER is the efficiency obtained from said standard curve.
6. A system comprising a computer processor, and instructions that cause the processor to perform a procedure comprising the steps of:
a) receiving a plurality of measurements obtained from a plurality of standard templates;
b) receiving a plurality of measurements obtained from a target template;
c) estimating a cycle threshold (Ct) value for each of said plurality of standard templates and said target template, wherein the Ct value is estimated by a method comprising the steps, for each set of measurements for each said template, of:
i) compiling a candidate list of all sets of consecutive signal measurements with cardinality 3 or greater;
ii) removing those signal measurements from said candidate list for which peak area measurement is less than peak area measurement at the previous cycle;
iii) computing a best-fitting line by linear regression for each set of measurements, said line representing a log-linear amplification curve described by equation (1):
log(measured value)=C0+EC
wherein C is the cycle number, C0 is the X intercept and E is the slope of the line;
iv) computing a fitness score for each of said target nucleic acid and said plurality of standards, wherein the fitness score is computed as a weighted sum of the correlation coefficient of the regression computed in step (iii), the cardinality of the candidate data set, and proximity to the fluorescence threshold;
v) selecting the set with the highest fitness score as the best set for each of said target nucleic acid and said plurality of standards; and
vi) computing Ct from the best set from each of said target nucleic acid and said plurality of standards, wherein Ct is computed by:
A) choosing a threshold value for log(measured value) of equation (1)
B) solving equation (1) for C when log(measured value) equals the chosen threshold value, C0 equals the X intercept determined in step (c)(iii) and E equals the slope determined in step (c)(iii);
C) setting Ct equal to the solved value of C;
d) generating a standard curve by plotting Ct values estimated in step (c) on the y axis for each of said plurality of said standard templates versus the log of said known copy number on the x axis for each said standard template; and
e) calculating an initial concentration (Q0) for said target nucleic acid template by solving the equation
C
t
\u2061
(
target
)
=
I
–
log
\u2061
(
Q
0
)
log
\u2061
(
E
R
)
for Q0, wherein I is the X intercept of said standard curve and ER is the efficiency obtained from said standard curve.