Matching of mass spectra when peak height is encoded to one bit

Grotch, Stanley L.

doi:10.1021/ac60293a007

Cited by 95 publications

(38 citation statements)

References 10 publications

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“…In some previous studies (13), spectral intensities have been encoded only to one bit. That is, each wavelength chaninel is assigned an intensity of "1" for peak present, or "0" for peak absent.…”

Section: Theory Definition Of a Spectrum And Comparison Metric A Spementioning

confidence: 99%

“…The AND function was used initially (18) since this measures similarity and is the most obvious choice. The exclusive OR function (XOR) measures dissimilarity, and more importantly XOR is the binary analog of least squares, which lends a certain theoretical justification to its use (13,19). Combinations of Boolean functions have also been used for library searching.…”

Section: Evaluation Of Several Boolean Based Comparison Metricsmentioning

confidence: 99%

“…Lam and co-workers (15) used the complement of the XOR as a similarity metric, calling it EXNOR, exclusive NOR. Grotch (13,20) used a linear combination of XOR and AND, XOR-K AND, where p was intuitively set equal to 2.…”

Section: Evaluation Of Several Boolean Based Comparison Metricsmentioning

confidence: 99%

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Quantitative evaluation of library searching performance

Delaney¹,

Warren²,

Hallowell³

1983

Anal. Chem.

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A procedure Is descrlbed for the quantltatlve evaluatlon of the performance of a llbrary searchlng system employed for molecular structure elucldatlon. The technlque allows the evaluatlon of any form of spectral representation or any spectral comparison metrlc. The approach Is applicable to any type of spectrometry used for llbrary searchlng (LS) or to comblnatlons of different types of spectra. All comparisons are made relative to a chosen standard of quallty for library searching performance. I t Is assumed that the results of searchlng a llbrary of full-Intensity, full-resolution spectra by a least-squares metrlc will provlde an acceptable standard for comparlson. Results are presented to demonstrate the utlllty of thls procedure for the examlnatlon of alternatlves for llbrary searching of vapor-phase Infrared spectra.Library searching (LS) has been used effectively for both the identification and interpretation of spectra. The continued interest in instruments such as the gas chormatography/ Fourier transform infrarled spectrometer (GC/FTIR) underscores the need for an objective approach to the development of versatile and efficient LS systems. The tremendous quantity of data which can be generated in a single GC/FTIR experiment necessitates computer-assisted data processing.Consequently, 1,s systems are included in most commercial GC/FTIR instruments.Two important choices must be made in the design of a library searching system: (1) the manner in which the spectra are to be processed prior to storage in the reference library, and (2) the comparison >metric to be used during the search. A diversity of options for each of these has appeared in the literature (1-9) but it is not clear what combination of options would provide the best L S system for a given application. As a result, the development of LS systems is typically approached empirically. Various possibilities are tried until "satisfactory" porformance is obtained. Commercial FTIR search systems reflect this problem, in that they generally offer a number of options for spectral processing and choice of search metric, with little guidance as to how to design an optimal searching system.The need for a quantitative evaluation of library searching systems has received some attention in the literature. LS systems designed for th,e identification of spectra are most easily treated. Here the goal is unambiguous. The search system succeeds if it gets the right answer. Quality for LS systems of this sort has been expressed as the percentage of correctly identified spectra (10).For interpretive LS systems, the problem is more complex. These systems are designed to give useful information for spectal interpretation even when the unknown spectrum is not present in the refer~ence library. The entire "hit-list" of closest matches thus becomes important in determining quality. The most cominon approach to assessing quality in such systems has been by subjective visual inspection of hit-lists (11). Such "evaluation by acclamation" is too qualitative to provide a soun...

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Section: Theory Definition Of a Spectrum And Comparison Metric A Spementioning

confidence: 99%

Section: Evaluation Of Several Boolean Based Comparison Metricsmentioning

confidence: 99%

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Quantitative evaluation of library searching performance

Delaney¹,

Warren²,

Hallowell³

1983

Anal. Chem.

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“…It is possible to prove that the two kinds of entropy defined above as related to two sets X and Y of analytical events before and after the experiment, are related by the equations: (21) (22) (23) H ( X ) I H ( X I Y ) (24) H(Y) 5 H(YIX) (25) In the last three equations, the equality stands when the events xi and yj of sets X and Yare independent, i.e., the following condition is fulfilled:…”

Section: Referring T O T H E Case Of a N Analytical Experiments Of Detmentioning

confidence: 99%

Utilization of the amount of information in evaluation of analytical methods

Liteanu¹,

Rica²

1979

Anal. Chem.

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The goal of analytical processes is to acquire chemical information and therefore the amount of information, according to Shannon, is the most adequate measure in the evaluation of an analytical process. The procedure of evaluating the amount of information In analytical processes as well as the utilization of this quantity as a criterion in solving many analytical problems is discussed; the problems are: selecting one method out of several methods, the optimal combination of several methods to solve an analytlcal problem, coding of information, and chemical classificatbn. The analogy between the systems of Information transmisslon and analytical measuring systems allows the adaptation of information theory notions (entropy, amount of information, coding, decoding, perturbatlons, etc.) to chemical analysis. This represents the generalized basis of analytical chemistry.(60-63).

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“…A lot of efforts [1][2][3][4][5][6][7][8][9][10][11] have been made in this field. Hertz 2 presented a very nice discussion.…”

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confidence: 99%

Library Search of Mass Spectra with a New Matching Algorithm Based on Substructure Similarity

2001

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Library searches of mass spectra are an important part of mass spectrum interpretation; they constitute the essential part of a mass spectra expert system. A lot of efforts [1][2][3][4][5][6][7][8][9][10][11] have been made in this field. Hertz 2 presented a very nice discussion. So far, two strategies of library searches have been widely accepted, the forward search and the reverse search 3 and the latter was strongly recommended. 7 However, there is still room for improvements in library searches of mass spectra. To our knowledge, there are at least two problems unsolved in the field of library search of mass spectra: 1) the spectrum of the unknown is not in the library, but only spectra of similar molecule structures; and 2) the spectrum of the unknown is not in the library and there are not similar ones in the library either. We will not discuss the second problem in this paper because it concerns the structural interpretation of mass spectra.The aim of this paper is to try to solve problem 1. To our knowledge, if the spectrum of the unknown compound is in the spectral library, it will match well with the target reference spectrum by existing methods without difficulty. However, if the spectrum of the unknown is not in the spectral library, the search results are not always good enough. In our opinion, a valid algorithm should include the following two features: 1) pick out the real one when the spectrum of the unknown is in the mass spectral library; 2) pick out the most structurally similar one when the spectrum of the unknown is not in the library. In this way, a similarity search can afford help to the manual or machine interpretation of mass spectrum of the unknown. In order to achieve the task discussed above, the correlation between spectral similarity and structural similarity was firstly clarified. Then, a novel but also simple similarity index was developed based on this. Finally, some experiments and comparisons of results with the ones from the commercial instrument of Shimadzu were conducted in order to show the superiority of our method. Theory and Methodology Mass spectra and structural similarityA similarity index is needed in order to assess the structure similarity. It is well known that the molecules of similar structure, in general, will give similar mass spectra. It is such a basis that makes the library search doable. If the similarity index has a value close to 100% (for instance, bigger than 90%), this means that they two are quite similar in molecular structure. Otherwise, the structures of the two molecules are taken as different. A new matching algorithm for library searches of mass spectra is presented in this paper. The algorithm is based on the substructure similarity of substances. It emphasizes m/z positions rather than abundance values. 32 spectra, whose corresponding molecular weights are less than 200, were randomly selected from a mass library of 61993 spectra and taken as targets of library search to illustrate the availability of this algorithm. The results show that the...

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Matching of mass spectra when peak height is encoded to one bit

Cited by 95 publications

References 10 publications

Quantitative evaluation of library searching performance

Quantitative evaluation of library searching performance

Utilization of the amount of information in evaluation of analytical methods

Library Search of Mass Spectra with a New Matching Algorithm Based on Substructure Similarity

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