Abstract:
An identification by mass spectrometry of a microorganism from among reference microorganisms represented by reference data sets includes: determining a set of data of the microorganism according to a spectrum; for each reference microorganism, calculating a distance between the determined and reference sets; and calculating a probability f(m) according to relation f ( m ) = pN ( m ❘ μ , σ ) pN ( m ❘ μ , σ ) + ( 1 - p ) N ( m ❘ μ _ , σ _ ) where: m is the distance calculated for the reference microorganism; N(m|μ,σ) is the value, for m, of a random variable modeling the distance between a reference microorganism to be identified and the reference microorganism, when the microorganism is the reference microorganism; N(m|μ,σ) is the value, for m, of a random variable modeling the distance between a microorganism to be identified and the reference microorganism, when the microorganism is not the reference microorganism; and p is a scalar in the range from 0 to 1.
Abstract:
The invention relates to a method for in vitro diagnosis or prognosis of testicular cancer which comprises a step of detecting the presence or absence of at least one expression product from at least one nucleic acid sequence selected from the sequences identified in SEQ ID NOS: 1 to 6 or from the sequences which exhibit at least 99% identity with one of the sequences identified in SEQ ID NOS: 1 to 6, to isolated nucleic acid sequences and to the use thereof as a testicular cancer marker.
Abstract:
A method for identifying by mass spectrometry an unknown microorganism subgroup among a set of reference subgroups, including a step of constructing one knowledgebase and one classifying model per associated subgroup on the basis of the acquisition of at least one set of learning spectra of microorganisms identified as belonging to the subgroups of a group and including: constructing an adjusting model allowing mass-to-charge offsets of the acquired spectra to be corrected on the basis of reference masses-to-charges that are common to the various subgroups; adjusting the masses-to-charges of all of the lists of peaks of the learning spectra and constructing one classifying model per subgroup and the associated knowledgebase on the basis of the adjusted learning spectra.
Abstract:
A method of identifying a microorganism by mass spectrometry, including acquiring at least one mass spectrum of said microorganism; for each acquired mass spectrum: detecting peaks of the spectrum in a predetermined mass range; generating a list of peaks identifying at most one peak in each interval of a predetermined subdivision of the range of mass-to-charge ratios, the width of the intervals of the subdivision logarithmically increasing along with the mass-to-charge ratio, and analyzing the list(s) of peaks obtained according to a knowledge base of previously-identified microorganisms and/or types of microorganisms.
Abstract:
A method of identifying a microorganism by mass spectrometry, including acquiring at least one mass spectrum of said microorganism; for each acquired mass spectrum: detecting peaks of the spectrum in a predetermined mass range; generating a list of peaks identifying at most one peak in each interval of a predetermined subdivision of the range of mass-to-charge ratios, the width of the intervals of the subdivision logarithmically increasing along with the mass-to-charge ratio, and analyzing the list(s) of peaks obtained according to a knowledge base of previously-identified microorganisms and/or types of microorganisms.
Abstract:
The invention relates to a method for in vitro diagnosis or prognosis of testicular cancer which comprises a step of detecting the presence or absence of at least one expression product from at least one nucleic acid sequence selected from the sequences identified in SEQ ID NOS: 1 to 6 or from the sequences which exhibit at least 99% identity with one of the sequences identified in SEQ ID NOS: 1 to 6, to isolated nucleic acid sequences and to the use thereof as a testicular cancer marker.
Abstract:
An identification by mass spectrometry of a microorganism from among reference microorganisms represented by reference data sets includes: determining a set of data of the microorganism according to a spectrum; for each reference microorganism, calculating a distance between the determined and reference sets; and calculating a probability f(m) according to relation f ( m ) = pN ( m μ , σ ) pN ( m μ , σ ) + ( 1 - p ) N ( m μ _ , σ _ ) where: m is the distance calculated for the reference microorganism; N(m|μ,σ) is the value, for m, of a random variable modeling the distance between a reference microorganism to be identified and the reference microorganism, when the microorganism is the reference microorganism; N(m| μ, σ) is the value, for m, of a random variable modeling the distance between a microorganism to be identified and the reference microorganism, when the microorganism is not the reference microorganism; and p is a scalar in the range from 0 to 1.
Abstract:
An identification by mass spectrometry of a microorganism from among reference microorganisms represented by reference data sets includes: determining a set of data of the microorganism according to a spectrum; for each reference microorganism, calculating a distance between the determined and reference sets; and calculating a probability ƒ(m) according to relation
f
( m )
=
pN
(
m | μ
, σ
)
pN
(
m | μ
, σ
)
+
(
1 - p
)
N
(
m |
μ _
,
σ _
)
where: m is the distance calculated for the reference microorganism; N(m|μ,σ) is the value, for m, of a random variable modeling the distance between a reference microorganism to be identified and the reference microorganism, when the microorganism is the reference microorganism; N(m|μ,σ) is the value, for m, of a random variable modeling the distance between a microorganism to be identified and the reference microorganism, when the microorganism is not the reference microorganism; and p is a scalar in the range from 0 to 1.
Abstract:
The invention relates to a method for in vitro diagnosis or prognosis of testicular cancer which comprises a step of detecting the presence or absence of at least one expression product from at least one nucleic acid sequence selected from the sequences identified in SEQ ID NOS: 1 to 6 or from the sequences which exhibit at least 99% identity with one of the sequences identified in SEQ ID NOS: 1 to 6, to isolated nucleic acid sequences and to the use thereof as a testicular cancer marker.
Abstract:
A method of identifying a microorganism by mass spectrometry, including acquiring at least one mass spectrum of said microorganism; for each acquired mass spectrum: detecting peaks of the spectrum in a predetermined mass range; generating a list of peaks identifying at most one peak in each interval of a predetermined subdivision of the range of mass-to-charge ratios, the width of the intervals of the subdivision logarithmically increasing along with the mass-to-charge ratio, and analyzing the list(s) of peaks obtained according to a knowledge base of previously-identified microorganisms and/or types of microorganisms.