Computer searching of infrared spectra using peak location and intensity data

Fox, Rosa

doi:10.1021/ac60368a027

Cited by 33 publications

(6 citation statements)

References 29 publications

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“…Two absorbance derivatizing reagents are also used in amino acid analysis: phenyl isothiocyanate (PITC) and 4-(dimethylamino)azobenzene-4'-sulfonyl (DABSYL) chloride (5,6). PITC is the reagent utilized in the classic Edman degradation scheme for protein sequencing.…”

Section: Acknowledgmentmentioning

confidence: 99%

“…Improved infrared spectral digitization was attained by using devices for translating hard-copy plots into digital format (3,4). Binary information can be augmented with band intensity (5,6) as well as width designations (7,8). Augmented binary representations contain qualitative band intensity information encoded by using numbers to indicate relative magnitude (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Deconvoluted band representation for infrared spectrum compression

Divis¹,

White²

1989

Anal. Chem.

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Section: Acknowledgmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Deconvoluted band representation for infrared spectrum compression

Divis¹,

White²

1989

Anal. Chem.

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“…when the summation is evaluated. The figure of merit is defined so that a value of 0% is obtained for the worst case and 100% for the best (7) Example. A specific hypothetical example will help to clarify this evaluation process.…”

Section: S= Hj (3) I=v=imentioning

confidence: 99%

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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“…

Sir: A wide variety of computer systems for the retrieval and interpretation of unknown spectra, especially mass spectra, have been proposed in recent years (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14). Reliable ways to evaluate these systems are necessary both to develop further improvements and to allow the user to choose the best system for his needs.

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mentioning

confidence: 99%