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Computer software (or simply software) is the programs and procedures that enable a computer to perform a specific task, as opposed to the physical components of the system (hardware). This includes application software such as a word processor, which enables a user to perform a task, and system software such as an operating system, which enables other software to run properly, by interfacing with hardware and with other software.

The term "software" was first used in this sense by John W. Tukey in 1957. In computer science and software engineering, computer software is all information processed by computer systems, programs and data. The concept of reading different sequences of instructions into the memory of a device to control computations was invented by Charles Babbage as part of his difference engine. The theory that is the basis for most modern software was first proposed by Alan Turing in his 1935 essay Computable numbers with an application to the Entscheidungsproblem. Hally, Mike (2005:79). Electronic brains/Stories from the dawn of the computer age. British Broadcasting Corporation and Granta Books, London. ISBN 1-86-207663-4.

Relationship to hardware


Computer software is so called in contrast to computer hardware, which encompasses the physical interconnections and devices required to store and execute (or run) the software. In computers, software is loaded into RAM and executed in the central processing unit. At the lowest level, software consists of a machine language specific to an individual processor. A machine language consists of groups of binary values signifying processor instructions (object code), which change the state of the computer from its preceding state. Software is an ordered sequence of instructions for changing the state of the computer hardware in a particular sequence. It is generally written in high-level programming languages that are easier and more efficient for humans to use (closer to natural language) than machine language. High-level languages are compiled or interpreted into machine language object code. Software may also be written in an assembly language, essentially, a mnemonic representation of a machine language using a natural language alphabet. Assembly language must be assembled into object code via an assembler.

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Clinical Chemistry current issue

[Editorials] Protein Quantitation through Targeted Mass Spectrometry: The Way Out of Biomarker Purgatory?
Carr, S. A., Anderson, L. Tue, 28 Oct 2008 00:00:00 -0000

[Editorials] Screening Algorithms for Monoclonal Gammopathies
Katzmann, J. A., Dispenzieri, A. Tue, 28 Oct 2008 00:00:00 -0000

[Perspective] Translating Hemoglobin A1c into Average Blood Glucose: Implications for Clinical Chemistry
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[Reviews] Current Status of Salivary Hormone Analysis
Groschl, M. Tue, 28 Oct 2008 00:00:00 -0000
Background: Saliva, which offers a noninvasive and stress-free alternative to plasma and serum, is a widely accepted sample source for analysis of steroids and also of certain amines and peptides. In recent years, numerous publications have described the use of salivary hormone analysis in many fields of clinical and basic research. Content: This review provides an overview of the current applications of salivary hormone analysis. A description of the different modes of hormone entry into saliva is followed by a detailed description of analytical methods and approaches for reliable collection of saliva, including several interesting applications in diverse fields including psychiatry, stress research, clinical endocrinology, sports medicine, and veterinary medicine. Summary: Although saliva has not yet become a mainstream sample source for hormone analysis, it has proven to be reliable and, in some cases, even superior to other body fluids. Nevertheless much effort will be required for this approach to receive acceptance over the long term, especially by clinicians. Such effort includes the development of specific and standardized analytical tools, the establishment of defined reference intervals, and implementation of round-robin trials. One major problem, the lack of compliance sometimes seen in outpatient saliva donors, requires strict standardization of both collection and analysis methods to achieve better comparability and assessment of published salivary hormone data.
[Reviews] A Personalized Approach to Cancer Treatment: How Biomarkers Can Help
Duffy, M. J., Crown, J. Tue, 28 Oct 2008 00:00:00 -0000
Background: The present approach to cancer treatment is often referred to as "trial and error" or "one size fits all." This practice is inefficient and frequently results in inappropriate therapy and treatment-related toxicity. In contrast, personalized treatment has the potential to increase efficacy and decrease toxicity. Content: We reviewed the literature relevant to prognostic, predictive, and toxicity-related markers in cancer, with particular attention to systematic reviews, prospective randomized trials, and guidelines issued by expert panels. To achieve personalized treatment for cancer, we need markers for determining prognosis, predicting response to therapy, and predicting severe toxicity related to treatment. Among the best-validated prognostic markers currently available are serum concentrations of -fetoprotein (AFP), human chorionic gonadotropin (hCG), and lactate dehydrogenase (LDH) for patients with nonseminoma germ cell tumors and tissue concentrations of both urokinase plasminogen activator and plasminogen activator inhibitor 1 (PAI-1) for breast cancer patients. Clinically useful therapy predictive markers are estrogen and progesterone receptors to select patients with breast cancer for treatment with endocrine therapy and human epidermal growth factor receptor 2 (HER-2) to select breast cancer patients for treatment with trastuzumab (Herceptin). Markers available for identifying drug-induced adverse reactions include thiopurine methyltransferase (TPMT) to predict toxicity from thiopurines in the treatment of acute lymphoblastic leukemia and uridine diphosphate glucuronyltransferase to predict toxicity from irinotecan in the treatment of colorectal cancer. Conclusions: Validated prognostic, predictive, and toxicity markers should help cancer treatment move from the current trial-and-error approach to more personalized treatment.
[Proteomics and Protein Markers] Impact of Epitope Specificity and Precursor Maturation in Pro-B-Type Natriuretic Peptide Measurement
Goetze, J. P., Dahlstrom, U., Rehfeld, J. F., Alehagen, U. Tue, 28 Oct 2008 00:00:00 -0000
Background: Cardiac-derived natriuretic peptides are sensitive plasma markers of cardiac dysfunction. Recent reports have disclosed a more complex molecular heterogeneity of B-type natriuretic peptide precursor (proBNP)-derived peptides than previously suggested. In this study, we examined the impact of epitope specificity and precursor maturation on plasma measurement of proBNP-derived peptides. Methods: We compared 2 assays, N-terminal proBNP and proBNP 1–76, in a randomly collected set of human plasma specimens (n = 370). Additionally, we evaluated the clinical performance of 4 assays with different epitope specificities in a cohort of elderly patients presenting with symptoms associated with heart failure (n = 415). Results: Comparison of N-terminal proBNP with proBNP 1–76 measurement in plasma revealed a high correlation on regression analysis (r2 = 0.91, P < 0.0001). Nevertheless, the proBNP 1–76 assay measured lower concentrations in the high range than the N-terminal proBNP assay. Correlations between assay measurements in a clinical setting were comparable for all the assays (r2 approximately 0.57–0.83), and ROC analyses revealed area-under-the-curve values ranging between 0.77 and 0.81 for identifying reduced left ventricular ejection fraction. In parallel, all assays displayed comparable abilities in predicting long-term mortality. Conclusions: Our results reveal marked assay differences in analytical assay comparison, contrasting the overall comparable clinical performance in cardiovascular diagnostics or prognosis in the elderly.

 
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ATNOS/CANDID program - Application suite for automated NOESY spectral analysis.

CARA - Computer Aided Resonance Assignment - An for application the analysis of NMR spectra and resonance assignment developed at Prof. Kurt Wüthrich's group.

GARANT - General Algorithm for Resonance AssignmeNT - GARANT is an algorithm for automatic resonance assignment using as input the primary structure of a protein

NMRView - Software for the visualization and analysis of NMR data

Pronto - is a tool for assignment of multidimensional spectra of macromolecules
Meta Description: [ Home page for Pronto. Software for analysis of NMR spectra of proteins. This free software takes you from the spectra to the list of constraints used in a molecular simulations calculation of a protein structure. ]

Sparky - A free C++ program for NMR display, assignment, peak integration, and analysis, which runs on multiple platforms.

XEASY - A C program, that runs on X-Windows, performs spectral analysis and automated spectroscopy.

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