A BASIC program for use in teaching population dynamics

This interactive simulation model can be used to demonstrate population growth with discrete or overlapping generations and the effects of random, constant, or density-dependent mortality.     

A BASIC computer program for analyzing endpoint assays.

We present a computer program that is based on Karber's approximation of endpoint titers, written in GW-BASIC and provides an easy means for analyzing the results of dilution endpoint assays. The program provides estimates of standard error that are not possible from other statistical procedures for this type of data.     

A BASIC program package for weighted least squares solutions using a microprocessor with disc memory

The fitting of linear additive models to data by weighted least squares methods has been programmed in BASIC. By splitting up the matrix solution into several steps, the RAM memory space needed in a microprocessor by the corresponding programs was reduced, allowing room for larger matrices. Storage of intermediate products, and of subsequent programs in the sequence, was on a mini floppy dual-disc drive. Using an extended BASIC interpreter permitting several files to be open during a program, the program package compromised between computing time and problem size. Problems involving 1600 element matrices were run on a micro having 32 000 bytes of memory, allowing, for example, the fitting of a model with 22 parameters to 72 observations.     

A non-linear regression program in BASIC for estimating Km and Vmax

This paper gives a program in BASIC for calculating the kineticparameters K_m and V_max for an enzyme reaction from a set ofpaired values of reaction velocity at given substrate concentrations.An initial estimate of the two parameters is made using a weightedlinear regression, these values are then used in an iterativeprocess to fit the data to the Michaelis–Menten equationand give final values of K_m and V_max with their associated standarderrors. Received on July 15, 1986; accepted on November 13, 1986     

REPLI: A program in BASIC for determination of approximate sample size

REPLI, a program written in elementary BASIC, calculates the approximate sample size, which is required to detect a desired difference between any two group means in an experiment with n groups for a given probability and at three significance levels of the means difference. A prior knowledge of the variability of data in the groups is expected in order to base the estimate on a rational footing. If this knowledge does not exist, an educated guess and/or several trials with different assumptions on the most likely variability can be used. The a priori estimate prevents that sample sizes are completely out of a reasonable range. Since the program is applicable for experimental settings where several groups need be investigated, it is particularly interesting to users of ANOVA and/or comparable non-parametric tests.     

A BASIC microcomputer program to calculate the secondary structure of proteins from their circular dichroism spectrum

A BASIC program (CDPROT) has been developed to calculate thesecondary structure of proteins from their far UV circular dichroismspectrum. This implementation can use different reference spectra,calculated either from model polypeptides or proteins of knowntertiary structure. Apart from obtaining the a-helical, ß-structure,ß-turns or random percentages which would generatethe spectrum of best fit with respect to the experimental measures,CDPROT represents on screen both theoretical and experimentalspectra indicating the root-mean-square error. The provisionof additional reference spectra by the user is also considered,and another program (STOREREF) performs the editing in an adequateformat for CDPROT. Received on March 8, 1988; accepted on June 3, 1988     

A computer program for Wiener filtering of evoked potential data.

We have developed a computer program for Wiener filtering of evoked potential data. The basic algorithm involves computation of the difference berween the power spectrum of the sweep sum and the sum of power spectra of individual sweeps. Power spectra are computed by means of the discrete Fourier transform. The program is now being run on a LSI-11 computer in a neurophysiology research laboratory to analyze somatic evoked potential data from monkeys.     

BASIC program for reduction of data from community-level physiological profiling using biolog microplates: rationale and critical interpretation of data

A BASIC program is offered that reduces data resulting from mixed-species inoculations into Biolog microplates. The procedures of the program are supported by a critical review of the literature relating to Biolog data reduction. The availability of standardized, accelerated data reduction protocols will facilitate study comparisons and allow efficient evaluation of new data reduction approaches.     

Selective removal of molybdenum traces from growth media of N2-fixing bacteria

A new method for the selective removal of traces of molybdenum from growth media of N2-fixing bacteria (Rhodobacter capsulatus and Klebsiella pneumoniae) was developed. This method is based on the filtration of nutrient solutions through a layer of activated carbon (pulverized charcoal). The adsorption of Mo (molybdate) to activated carbon was optimal if a charcoal suspension (50 g/liter) was degassed by boiling before use and if the pH of the solutions, which had to be purified, was adjusted to values between 1.5 and 4. In this pH region no or only negligible amounts of other metal ions were adsorbed. The activated carbon method was compared with other Mo-eliminating procedures, including 8-hydroxyquinoline/dichloromethane extraction, Chelex 100 chromatography, and treatment with Mo-starved Azotobacter vinelandii cells. The activated carbon filtration appeared to be the most effective, specific, and rapid method. Whereas the untreated Rhodobacter growth medium was contaminated with 1.2 ppb Mo, as analyzed by inductively coupled plasma mass spectrometry (ICP-MS), the activated carbon-treated medium was below the ICP-MS detection limit (less than 0.05 ppb). A similarly effective removal of Mo impurities was obtained by the Azotobacter treatment. Even at low optical densities (2-5 at 436 nm) Mo traces were removed very rapidly within 10-15 min. However, because the Mo uptake/Mo adsorption capacity of A. vinelandii depended on freshly cultivated cells and on the growth phase at which the cells were harvested, this microbiological method was generally more time-consuming and less reproducible than the activated carbon method.(ABSTRACT TRUNCATED AT 250 WORDS)     

A BASIC microcomputer program for prediction of B and T cell epitopes in proteins

A BASIC microcomputer program (EPIPLOT) has been developed forpredicting B and T cell antigenic sites in proteins from theirprimary structures. The program calculates and plots flexibility,hydrophilicity and antigenicity profiles using 13 differentscales, chosen as those yielding the best predictions on proteinswhose antigenic structures are known. T cell epitope predictionis basedon published algorithms focused on amphiphilic structuresand characteristic sequence patterns. The advantages of jointpredictions in locating T cell antigenic sites are also discussed. Received on December 12, 1989; accepted on January 31, 1990     

A novel peak detection approach with chemical noise removal using short‐time FFT for prOTOF MS data

Peak detection is a pivotal first step in biomarker discovery from MS data and can significantly influence the results of downstream data analysis steps. We developed a novel automatic peak detection method for prOTOF MS data, which does not require a priori knowledge of protein masses. Random noise is removed by an undecimated wavelet transform and chemical noise is attenuated by an adaptive short‐time discrete Fourier transform. Isotopic peaks corresponding to a single protein are combined by extracting an envelope over them. Depending on the S/N, the desired peaks in each individual spectrum are detected and those with the highest intensity among their peak clusters are recorded. The common peaks among all the spectra are identified by choosing an appropriate cut‐off threshold in the complete linkage hierarchical clustering. To remove the 1 Da shifting of the peaks, the peak corresponding to the same protein is determined as the detected peak with the largest number among its neighborhood. We validated this method using a data set of serial peptide and protein calibration standards. Compared with MoverZ program, our new method detects more peaks and significantly enhances S/N of the peak after the chemical noise removal. We then successfully applied this method to a data set from prOTOF MS spectra of albumin and albumin‐bound proteins from serum samples of 59 patients with carotid artery disease compared to vascular disease‐free patients to detect peaks with S/N≥2. Our method is easily implemented and is highly effective to define peaks that will be used for disease classification or to highlight potential biomarkers.     

A fast DNA sequence handling program for Apple II computer in BASIC and 6502 assembler

A fast general purpose DNA handling program has been developedin BASIC and machine language. The program runs on the AppleII plus or on the Apple IIe microcomputer, without additionalhardware except for disk drives and printer. The program allowsfile insertion and editing, translation into protein sequence,reverse translation, search for small strings and restrictionenzyme sites. The homology may be shown either as a comparisonof two sequences or through a matrix on screen. Two additionalfeatures are: (i) drawing restriction site maps on the printer;and (ii) simulating a gel electrophoresis of restriction fragmentsboth on screen and on paper. All the operations are very fast.The more common tasks are carried out almost instantly; onlymore complex routines, like finding homology between large sequencesor searching and sorting all the restriction sites in a longsequence require longer, but still quite acceptable, times (generallyunder 30 s). Received on October 25, 1984; accepted on December 7, 1984     

Blind noise reduction for multisensory signals using ICA and subspace filtering, with application to EEG analysis

 In many applications of signal processing, especially in communications and biomedicine, preprocessing is necessary to remove noise from data recorded by multiple sensors. Typically, each sensor or electrode measures the noisy mixture of original source signals. In this paper a noise reduction technique using independent component analysis (ICA) and subspace filtering is presented. In this approach we apply subspace filtering not to the observed raw data but to a demixed version of these data obtained by ICA. Finite impulse response filters are employed whose vectors are parameters estimated based on signal subspace extraction. ICA allows us to filter independent components. After the noise is removed we reconstruct the enhanced independent components to obtain clean original signals; i.e., we project the data to sensor level. Simulations as well as real application results for EEG-signal noise elimination are included to show the validity and effectiveness of the proposed approach. Received: 6 November 2000 / Accepted in revised form: 12 November 2001     

Spectral processing methods for the removal of t1 noise and solvent artifacts from NMR spectra

Summary A data processing method is described which reduces the effects of t₁ noise artifacts and improves the presentation of 2D NMR spectral data. A t₁ noise profile is produced by measuring the average noise in each column. This profile is then used to determine weighting coefficients for a sliding weighted smoothing filter that is applied to each row, such that the amount of smoothing each point receives is proportional to both its estimated t₁ noise level and the level of t₁ noise of neighbouring points. Thus, points in the worst t₁ noise bands receive the greatest smoothing, whereas points in low-noise regions remain relatively unaffected. In addition, weighted smoothing allows points in low-noise regions to influence neighbouring points in noisy regions. This method is also effective in reducing the noise artifacts associated with the solvent resonance in spectra of biopolymers in aqueous solution. Although developed primarily to improve the quality of 2D NMR spectra of biopolymers prior to automated analysis, this approach should enhance processing of spectra of a wide range of compounds and can be used whenever noise occurs in discrete bands in one dimension of a multi-dimensional spectrum.