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J Engelbrecht

Publications and source records attributed to J Engelbrecht.

28 records · Page 2Linked to original sources
PubMed1992

G+C-rich tract in 5' end of human introns.

Analysis of an artificial neural network trained to classify DNA as coding or non-coding revealed compositional differences between sequence parts translated into protein and those that were not. The 5' end of human introns was found to have a base composition that was non-random to an extent matching the non-randomness in the 3' end that contains the polypyrimidine tract. The prevailing nucleotides in the initial 50 nucleotides of human introns are guanine and cytosine, the trinucleotide GGG was found to occur almost four times as frequently as it would in sequences with a uniform distribution of the nucleotides. The initial part of terminal exons and their associated terminal introns were shown to have a very special base composition deviating strongly from the normal picture in other exons and introns.

Base Composition↗
PubMed1992

Multiple alignment using simulated annealing: branch point definition in human mRNA splicing.

A method for the simultaneous alignment of a very large number of sequences using simulated annealing is presented. The total running time of the algorithm does not depend explicitly on the number of sequences treated. The method has been used for the simultaneous alignment of 1462 human intron sequences upstream of the intron-exon boundary. The consensus sequence of the aligned set together with a calculation of the Shannon information clearly shows that several sequence motives are conserved: (i) a previously undetected guanosine rich region, (ii) the branch point and (iii) the polypyrimidine tract. The nucleotide frequencies at each position of the branch point consensus sequence qualitatively reproduce the frequencies of the experimentally determined branch points.

Algorithms↗
PubMed1991

Prediction of human mRNA donor and acceptor sites from the DNA sequence.

Artificial neural networks have been applied to the prediction of splice site location in human pre-mRNA. A joint prediction scheme where prediction of transition regions between introns and exons regulates a cutoff level for splice site assignment was able to predict splice site locations with confidence levels far better than previously reported in the literature. The problem of predicting donor and acceptor sites in human genes is hampered by the presence of numerous amounts of false positives: here, the distribution of these false splice sites is examined and linked to a possible scenario for the splicing mechanism in vivo. When the presented method detects 95% of the true donor and acceptor sites, it makes less than 0.1% false donor site assignments and less than 0.4% false acceptor site assignments. For the large data set used in this study, this means that on average there are one and a half false donor sites per true donor site and six false acceptor sites per true acceptor site. With the joint assignment method, more than a fifth of the true donor sites and around one fourth of the true acceptor sites could be detected without accompaniment of any false positive predictions. Highly confident splice sites could not be isolated with a widely used weight matrix method or by separate splice site networks. A complementary relation between the confidence levels of the coding/non-coding and the separate splice site networks was observed, with many weak splice sites having sharp transitions in the coding/non-coding signal and many stronger splice sites having more ill-defined transitions between coding and non-coding.

Base Sequence↗
PubMed1990

Neural network detects errors in the assignment of mRNA splice sites.

The use of databanks in genetic research assumes reliability of the information they contain. Currently, error-detection in the manually or electronically entered data contained in the nucleotide sequence databanks at EMBL, Heidelberg and GenBank at Los Alamos is limited. We have used a subset of sequences from these databanks to train neural networks to recognize pre-mRNA splicing signals in human genes. During the training on 33 human genes from the EMBL databank seven genes appeared to disturb the learning process. Subsequent investigation revealed discrepancies from the original published papers, for three genes. In four genes, we found wrongly assigned splicing frames of introns. We believe this to be a reflection of the fact that splicing frames cannot always be unambiguously assigned on the basis of experimental data. Thus incorrect assignment appear both due to mere typographical misprints as well as erroneous interpretation of experiments. Training on 241 human sequences from GenBank revealed nine new errors. We propose that such errors could be detected by computer algorithms designed to check the consistency of data prior to their incorporation in databanks.

Algorithms↗
PubMedDate not supplied

A neural network method for identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites.

We have developed a new method for the identification of signal peptides and their cleavage sites based on neural networks trained on separate sets of prokaryotic and eukaryotic sequences. The method performs significantly better than previous prediction schemes, and can easily be applied to genome-wide data sets. Discrimination between cleaved signal peptides and uncleaved N-terminal signal-anchor sequences is also possible, though with lower precision. Predictions can be made on a publicly available WWW server: http://www.cbs.dtu.dk/services/SignalP/.

Algorithms↗
PubMedDate not supplied

[Medical education, graduate and continuing education of physicians in geriatrics in Germany--current status].

Due to the importance of geriatrics which has been generally accepted in the inpatient medical care for many years, geriatrics has now been included into the amended Model Regulations of Postgraduate Medical Training (novellierte Muster-Weiter-bildungsordnung) in the form of the optional postgraduate training "clinical geriatrics". Thus geriatrics has the chance of being broadly accepted and standing the test in clinic and practice where our colleagues are working.

Aged↗