@article {1544,
	title = {Automated estimation of white Gaussian noise level in a spectrum with or without spike noise using a spectral shifting technique},
	journal = {Applied Spectroscopy},
	volume = {60},
	number = {7},
	year = {2006},
	note = {ISI Document Delivery No.: 063UWTimes Cited: 0Cited Reference Count: 19Schulze, H. Georg Yu, Marcia M. L. Addison, Christopher J. Blades, Michael W. Turner, Robin F. B.},
	month = {Jul},
	pages = {820-825},
	type = {Article},
	abstract = {Various tasks, for example, the determination of signal-to-noise ratios, require the estimation of noise levels in a spectrum. This is generally accomplished by calculating the standard deviation of manually chosen points in a region of the spectrum that has a flat baseline and is otherwise devoid of artifacts and signal peaks. However, an automated procedure has the advantage of being faster and operator-independent. In principle, automated noise estimation in a single spectrum can be carried out by taking that spectrum, shifting a copy thereof by one channel, and subtracting the shifted spectrum from the original spectrum. This leads to an addition of independent noise and a reduction of slowly varying features such as baselines and signal peaks; hence, noise can be more readily determined from the difference spectrum. We demonstrate this technique and a spike-discrimination variant on white Gaussian noise, in the presence and absence of spike noise, and show that highly accurate results can be obtained on a series of simulated Raman spectra and consistent results obtained on real-world Raman spectra. Furthermore, the method can be easily adapted to accommodate heteroscedastic noise.},
	keywords = {ALGORITHM, automated noise determination, DETECTION LIMITS, limit of detection, NOISE, noise estimation, RAMAN, REMOVAL, signal-to-noise ratio, spectral noise, standard deviation},
	isbn = {0003-7028},
	url = {<Go to ISI>://000239046400016},
	author = {Schulze, H. G. and Yu, M. M. L. and Addison, C. J. and Blades, M. W. and Turner, R. F. B.}
}
@article {1544,
	title = {Automated estimation of white Gaussian noise level in a spectrum with or without spike noise using a spectral shifting technique},
	journal = {Applied Spectroscopy},
	volume = {60},
	number = {7},
	year = {2006},
	note = {ISI Document Delivery No.: 063UWTimes Cited: 0Cited Reference Count: 19Schulze, H. Georg Yu, Marcia M. L. Addison, Christopher J. Blades, Michael W. Turner, Robin F. B.},
	month = {Jul},
	pages = {820-825},
	type = {Article},
	abstract = {Various tasks, for example, the determination of signal-to-noise ratios, require the estimation of noise levels in a spectrum. This is generally accomplished by calculating the standard deviation of manually chosen points in a region of the spectrum that has a flat baseline and is otherwise devoid of artifacts and signal peaks. However, an automated procedure has the advantage of being faster and operator-independent. In principle, automated noise estimation in a single spectrum can be carried out by taking that spectrum, shifting a copy thereof by one channel, and subtracting the shifted spectrum from the original spectrum. This leads to an addition of independent noise and a reduction of slowly varying features such as baselines and signal peaks; hence, noise can be more readily determined from the difference spectrum. We demonstrate this technique and a spike-discrimination variant on white Gaussian noise, in the presence and absence of spike noise, and show that highly accurate results can be obtained on a series of simulated Raman spectra and consistent results obtained on real-world Raman spectra. Furthermore, the method can be easily adapted to accommodate heteroscedastic noise.},
	keywords = {ALGORITHM, automated noise determination, DETECTION LIMITS, limit of detection, NOISE, noise estimation, RAMAN, REMOVAL, signal-to-noise ratio, spectral noise, standard deviation},
	isbn = {0003-7028},
	url = {<Go to ISI>://000239046400016},
	author = {Schulze, H. G. and Yu, M. M. L. and Addison, C. J. and Blades, M. W. and Turner, R. F. B.}
}
@article {1238,
	title = {Statistical evaluation of electrospray tandem mass spectra for optimized peptide fragmentation},
	journal = {Journal of the American Society for Mass Spectrometry},
	volume = {16},
	number = {4},
	year = {2005},
	note = {ISI Document Delivery No.: 911RDTimes Cited: 6Cited Reference Count: 33},
	month = {Apr},
	pages = {505-514},
	type = {Article},
	abstract = {Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has become the method of choice for the analysis of complex peptide mixtures. It combines the separation power of nanoflow LC with highly specific sequence analysis, allowing automated peptide sequencing with high resolution and throughput. For peptide fragmentation, the current experimental setup uses predefined parameters based on the mass-to-charge ratio of the individual precursor. Suitable parameters are typically established by empirical evaluation of fragment spectra of individual peptides used as standards. As a result, nonoptimal fragment spectra are obtained if peptides show fragmentation behavior different from these standards, which often result in the loss of sequence-specific fragment ion information. Here we describe a statistical approach for the systematic evaluation of the quality of individual peptide fragment spectra based on the calculation of their arithmetic mean and standard deviation. The method utilizes the dependence of these parameters on the difference in electric potential across the collision cell to determine the value that results in maximum information content. We show that the method is applicable to fragment spectra generated from a variety of multiply-charged tryptic peptides, over a wide concentration range, and on different types of mass analyzers. We also show how this novel approach can be used to define optimized collision energy settings over a wide mass-to-charge range. (J Am Soc Mass Spectrom 2005,16,505-514) (c) 2005 American Society for Mass Spectrometry},
	keywords = {ALGORITHM, ASSISTED-LASER-DESORPTION/IONIZATION, COLLISION-INDUCED DISSOCIATION, DATABASE SEARCH, MIXTURES, PROTEIN IDENTIFICATION, PROTEOMICS, PROTONATED PEPTIDES, SPECTROMETRY},
	isbn = {1044-0305},
	url = {<Go to ISI>://000228021400010},
	author = {Rogalski, J. C. and Lin, M. S. and Sniatynski, M. J. and Taylor, R. J. and Youhnovski, N. and Przybylski, M. and Kast, J.}
}
@article {4831,
	title = {Computational study of vertical ionization potentials using density functional theory and Green{\textquoteright}s function methods},
	journal = {Journal of the Chinese Chemical Society},
	volume = {47},
	number = {1},
	year = {2000},
	note = {ISI Document Delivery No.: 295BRTimes Cited: 6Cited Reference Count: 44},
	month = {Feb},
	pages = {141-147},
	type = {Article},
	abstract = {Over one hundred vertical ionization potentials (VIPs) were computed using density functional theory (DFT) and Green{\textquoteright}s function (GF) based methods. The DFT approaches include the unrestricted transition state (uTS) and unrestricted diffuse ionization (uDI) approximations using the Becke88-Perdew86 exchange-correlation functional. Green{\textquoteright}s function methods include the outer-valence GF (OVGF) approach, the parametrized GF2 (pGF2), and the parametrized GF2 times screened interaction (pGW2) approximations. DFT computations of IPs using the uTS approximation was found to be nearly as accurate as those predicted using the elaborate OVGF method. The much more computationally efficient uDI approximation provides predictions of moderate accuracy and is recommended for computing IPs for larger molecules. We have observed that the average absolute deviations from a uDI calculation using poorer basis set (DZVP) and poorer geometry (AM1 optimization) is only slightly larger.},
	keywords = {ALGORITHM, APPROXIMATION, density functional theory, ENERGIES, Green{\textquoteright}s function, MOLECULES, PHOTOELECTRON-SPECTRA, POTENTIALS, SPECTROSCOPY, vertical ionization},
	isbn = {0009-4536},
	url = {<Go to ISI>://000085946500016},
	author = {Hu, C. H. and Chong, D. P.}
}
