@article {2290,
	title = {Mass spectrometric identification of formaldehyde-induced peptide modifications under in vivo protein cross-linking conditions},
	journal = {Analytica Chimica Acta},
	volume = {618},
	number = {2},
	year = {2008},
	note = {ISI Document Delivery No.: 317FDTimes Cited: 10Cited Reference Count: 19Toews, Judy Rogalski, Jason C. Clark, Thomas J. Kast, Juergen},
	month = {Jun},
	pages = {168-183},
	type = {Article},
	abstract = {Formaldehyde cross-linking of proteins is emerging as a novel approach to study protein-protein interactions in living cells. It has been shown to be compatible with standard techniques used in functional proteomics such as affinity-based protein enrichment, enzymatic digestion, and mass spectrometric protein identification. So far, the lack of knowledge on formaldehyde-induced protein modifications and suitable mass spectrometric methods for their targeted detection has impeded the identification of the different types of crosslinked peptides in these samples. In particular, it has remained unclear whether in vitro studies that identified a multitude of amino acid residues reacting with formaldehyde over the course of several days are suitable substitutes for the much shorter reaction times of 10-20 min used in cross-linking experiments in living cells. The current study on model peptides identifies amino-termini as well as lysine, tryptophan, and cysteine side chains, i.e. a small subset of those modified after several days, as the major reactive sites under such conditions, and suggests relative position in the peptide sequence as well as sequence microenvironment to be important factors that govern reactivity. Using MALDI-MS, mass increases of 12 Da on amino groups and 30 Da on cysteines were detected as the major reaction products, while peptide fragment ion analysis by tandem mass spectrometry was used to localize the actual modification sites on a peptide. Non-specific cross-linking was absent, and could only be detected with low yield at elevated peptide concentrations. The detailed knowledge on the constraints and products of the formaldehyde reaction with peptides after short incubation times presented in this study is expected to facilitate the targeted mass spectrometric analysis of proteins after in vivo formaldehyde cross-linking. (c) 2008 Elsevier B.V. All rights reserved.},
	keywords = {Chemical modification, COMPLEXES, FORMALDEHYDE, MAP, mass, NETWORK, peptide fragmentation, protein cross-linking, PROTEOMICS, PURIFICATION, REACTIVITY, SPECTROMETRY},
	isbn = {0003-2670},
	url = {<Go to ISI>://000257004400006},
	author = {Toews, J. and Rogalski, J. C. and Clark, T. J. and Kast, J.}
}
@article {5127,
	title = {An aurophilicity-determined 3-D bimetallic coordination polymer: using [Au(CN)(2)](-) to increase structural dimensionality through gold center dot center dot center dot gold bonds in (tmeda)Cu[Au(CN)(2)](2)},
	journal = {Chemical Communications},
	number = {03},
	year = {2001},
	note = {ISI Document Delivery No.: 396KHTimes Cited: 68Cited Reference Count: 24},
	pages = {259-260},
	type = {Article},
	abstract = {A coordination polymer with the [Au(CN)(2)](-) building block has been prepared and it exhibits weak Au(I)-mediated ferromagnetic interactions; the structure illustrates that aurophilicity is a powerful tool to increase dimensionality, generating a three-dimensional system from a 1-D polymer.},
	keywords = {BUILDING-BLOCKS, CHEMISTRY, COMPONENT, CRYSTAL-STRUCTURE, LIGANDS, MAGNETIC-PROPERTIES, NETWORK},
	isbn = {1359-7345},
	url = {<Go to ISI>://000166635200017},
	author = {Leznoff, D. B. and Xue, B. Y. and Patrick, B. O. and Sanchez, V. and Thompson, R. C.}
}
@article {3510,
	title = {ARTIFICIAL NEURAL-NETWORK AND CLASSICAL LEAST-SQUARES METHODS FOR NEUROTRANSMITTER MIXTURE ANALYSIS},
	journal = {Journal of Neuroscience Methods},
	volume = {56},
	number = {2},
	year = {1995},
	note = {ISI Document Delivery No.: QH949Times Cited: 5Cited Reference Count: 28},
	month = {Feb},
	pages = {155-167},
	type = {Article},
	abstract = {Identification of individual components in biological mixtures can be a difficult problem regardless of the analytical method employed. In this work, Raman spectroscopy was chosen as a prototype analytical method due to its inherent versatility and applicability to aqueous media, making it useful for the study of biological samples. Artificial neural networks (ANNs) and the classical least-squares (CLS) method were used to identify and quantify the Raman spectra of the small-molecule neurotransmitters and mixtures of such molecules. The transfer functions used by a network, as well as the architecture of a network, played an important role in the ability of the network to identify the Raman spectra of individual neurotransmitters and the Raman spectra of neurotransmitter mixtures. Specifically, networks using sigmoid and hyperbolic tangent transfer functions generalized better from the mixtures in the training data set to those in the testing data sets than networks using sine functions. Networks with connections that permit the local processing of inputs generally performed better than other networks on all the testing data sets, and better than the CLS method of curve fitting, on novel spectra of some neurotransmitters. The CLS method was found to perform well on noisy, shifted, and difference spectra.},
	keywords = {ARTIFICIAL NEURAL, BACTERIA, CLASSICAL LEAST-SQUARES ANALYSIS, INVIVO VOLTAMMETRY, MIXTURE ANALYSIS, NETWORK, Raman spectroscopy, REGRESSION, SMALL-MOLECULE NEUROTRANSMITTER, SPECTRA, SYSTEM, UV RESONANCE RAMAN},
	isbn = {0165-0270},
	url = {<Go to ISI>://A1995QH94900006},
	author = {Schulze, H. G. and Greek, L. S. and Gorzalka, B. B. and Bree, A. V. and Blades, M. W. and Turner, R. F. B.}
}
@article {3510,
	title = {ARTIFICIAL NEURAL-NETWORK AND CLASSICAL LEAST-SQUARES METHODS FOR NEUROTRANSMITTER MIXTURE ANALYSIS},
	journal = {Journal of Neuroscience Methods},
	volume = {56},
	number = {2},
	year = {1995},
	note = {ISI Document Delivery No.: QH949Times Cited: 5Cited Reference Count: 28},
	month = {Feb},
	pages = {155-167},
	type = {Article},
	abstract = {Identification of individual components in biological mixtures can be a difficult problem regardless of the analytical method employed. In this work, Raman spectroscopy was chosen as a prototype analytical method due to its inherent versatility and applicability to aqueous media, making it useful for the study of biological samples. Artificial neural networks (ANNs) and the classical least-squares (CLS) method were used to identify and quantify the Raman spectra of the small-molecule neurotransmitters and mixtures of such molecules. The transfer functions used by a network, as well as the architecture of a network, played an important role in the ability of the network to identify the Raman spectra of individual neurotransmitters and the Raman spectra of neurotransmitter mixtures. Specifically, networks using sigmoid and hyperbolic tangent transfer functions generalized better from the mixtures in the training data set to those in the testing data sets than networks using sine functions. Networks with connections that permit the local processing of inputs generally performed better than other networks on all the testing data sets, and better than the CLS method of curve fitting, on novel spectra of some neurotransmitters. The CLS method was found to perform well on noisy, shifted, and difference spectra.},
	keywords = {ARTIFICIAL NEURAL, BACTERIA, CLASSICAL LEAST-SQUARES ANALYSIS, INVIVO VOLTAMMETRY, MIXTURE ANALYSIS, NETWORK, Raman spectroscopy, REGRESSION, SMALL-MOLECULE NEUROTRANSMITTER, SPECTRA, SYSTEM, UV RESONANCE RAMAN},
	isbn = {0165-0270},
	url = {<Go to ISI>://A1995QH94900006},
	author = {Schulze, H. G. and Greek, L. S. and Gorzalka, B. B. and Bree, A. V. and Blades, M. W. and Turner, R. F. B.}
}
