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PubMed1969

New medical library buildings. I. The Milton S. Hershey Medical Center Library of the Pennsylvania State University.

This paper discusses a new medical library. The physical plant, the development of the collection, and special activities are described. The budget is presented.

Architecture↗

PubMed1983

Roles for the library in information management. Making a dream come true: strategies for medical school libraries.

Academic medical school libraries are at different stages in implementing the recommendations of the Matheson report. Many have moved to higher-level tasks and are beginning to engage in the significant tasks described in the report; others are reviewing their future options. In the meantime, it is 6:00 P.M. of Mary Smith's first hospital day. How did we, as librarians, contribute to her diagnosis and treatment?

Information Services↗

PubMed2001

Library of FT-Raman spectra of pigments, minerals, pigment media and varnishes, and supplement to existing library of Raman spectra of pigments with visible excitation.

Sixty pigments, minerals and media have been analysed by Fourier-transform Raman (FT-Raman) microscopy in order to assemble a database of reference FT-Raman spectra for scientists working at the Arts-Science interface. An earlier library of Raman spectra compiled using visible excitation has been extended by the addition of 22 further reference spectra obtained with 780.0, 647.1, 632.8 and/or 514.5 nm excitation. The relative merits of 1064 nm and visible excitation are discussed.

Databases, Factual↗

PubMedDate not supplied

Rational combinatorial library design. 3. Simulated annealing guided evaluation (SAGE) of molecular diversity: a novel computational tool for universal library design and database mining.

We have developed a novel method for molecular diversity sampling called SAGE (simulated annealing guided evaluation of molecular diversity). Compounds in chemical databases or virtual combinatorial libraries are conventionally represented as points in multidimensional descriptor space. The SAGE algorithm selects a desired number of optimally diverse points (compounds) from a database. The diversity of a subset of points is measured by a specially designed diversity function, and the most diverse subset is selected using Simulated Annealing (SA) as the optimization tool. Application of SAGE to two simulated data sets of randomly distributed points in two-dimensional space afforded diverse and representative selection as judged by visual inspection. SAGE was also applied, in comparison with random sampling, to two other simulated data sets with points distributed among many clusters. We found that SAGE sampling covered significantly more clusters than the random sampling. By defining a fraction of data points as active, we also compared SAGE with random sampling in terms of hit rates. We showed that when the percentage of active points was low, the hit rates obtained by SAGE were always higher than those obtained by random sampling. When the percentage of active points was high, the performance of SAGE, in terms of individual hit rates, depended upon the data structure. However, in all cases, SAGE performed better than random sampling when cluster hit rates were used as the criterion.

Algorithms↗

PubMed2000

Cross-referenced combinatorial libraries for the discovery of metal-complexing ligands: library deconvolution by LC-MS.

N-Acylthioureas are excellent ligands for a variety of heavy metals, but their metal selectivity is highly dependent on the precise nature of the substituents present. In this paper we show how combinatorial chemistry techniques can be used to establish relative affinities for copper within a mixture of 100 such thioureas. Following a straightforward synthesis, and copper extraction using standard liquid-liquid extraction techniques, LC-MS was used to identify the ligands which bind most strongly to the copper ions. Among the 100 ligands XC(O)N(Z)C(S)NHY, the most important substituent is the Y group bound to the NH: only aromatic Y substituents give strong binding to copper. The acyl X substituents are invariably aromatic, and an electron-rich X group is best; the affinity for copper seems to be less dependent on the Z substituent, although a large group such as benzyl disfavours copper binding. The five ligands from the library which bind copper most strongly have been clearly identified by a series of experiments: they all have aromatic groups in the Y position, but the X and Z substituents can be more varied. This is a very convincing demonstration of the power of combinatorial methods: to have found the same information by conventional methods would have required a lengthy and repetitive series of syntheses and investigations. In addition, our results give some preliminary evidence for synergistic binding of two different ligands, but this requires further investigation.

Journal Article↗

PubMed1998