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Biology subjects

Boehm, C.

Publications and source records attributed to Boehm, C..

3 recordsLinked to original sources

varVAMP: automated pan-specific primer design for tiled full genome sequencing and qPCR of highly diverse viral pathogens.

Time- and cost-saving surveillance of viral pathogens is achieved by tiled sequencing in which a viral genome is amplified in overlapping PCR amplicons and qPCR. However, designing pan-specific primers for viral pathogens that have high genomic variability represents a major challenge. Here, we present a bioinformatics command-line tool, called varVAMP (variable virus amplicons). It relies on multiple sequence alignments of highly variable virus sequences and enables automatic pan-specific primer design for qPCR or tiled amplicon whole genome sequencing. The varVAMP software guarantees pan-specificity by two means: it designs primers in regions with minimal variability and introduces degenerate nucleotides into primer sequences to compensate for common sequence variations. We demonstrate varVAMPs utility by designing and evaluating novel pan-specific primer schemes suitable for sequencing the genomes of SARS-CoV-2, Hepatitis E virus, rat Hepatitis E virus, Hepatitis A virus, Borna-disease-virus-1, and Poliovirus. Moreover, we established highly sensitive and specific Poliovirus qPCR assays that could potentially simplify current Poliovirus surveillance. Importantly, wet-lab and bioinformatic techniques established for SARS-CoV-2 tiled amplicon sequencing were readily transferable to these new primer schemes and will allow sequencing laboratories to extend their established methodology to other human pathogens.

bioinformatics↗

Deep learning based decoding of local field potential events

How is information processed in the cerebral cortex? To answer this question a lot of effort has been undertaken to create novel and to further develop existing neuroimaging techniques. Thus, a high spatial resolution of fMRI devices was the key to exactly localize cognitive processes. Furthermore, an increase in time-resolution and number of recording channels of electro-physiological setups has opened the door to investigate the exact timing of neural activity. However, in most cases the recorded signal is averaged over many (stimulus) repetitions, which erases the fine-structure of the neural signal. Here, we show that an unsupervised machine learning approach can be used to extract meaningful information from electro-physiological recordings on a single-trial base. We use an auto-encoder network to reduce the dimensions of single local field potential (LFP) events to create interpretable clusters of different neural activity patterns. Strikingly, certain LFP shapes correspond to latency differences in different recording channels. Hence, LFP shapes can be used to determine the direction of information flux in the cerebral cortex. Furthermore, after clustering, we decoded the cluster centroids to reverse-engineer the underlying prototypical LFP event shapes. To evaluate our approach, we applied it to both neural extra-cellular recordings in rodents, and intra-cranial EEG recordings in humans. Finally, we find that single channel LFP event shapes during spontaneous activity sample from the realm of possible stimulus evoked event shapes. A finding which so far has only been demonstrated for multi-channel population coding.

neuroscience↗

Neural Correlates of Linguistic Collocations During Continuous Speech Perception

Language is fundamentally predictable, both on a higher schematic level as well as low-level lexical items. Regarding predictability on a lexical level, collocations are frequent co-occurrences of words that are often characterized by high strength of association. So far, psycho-and neurolin guistic studies have mostly employed highly artificial experimental paradigms in the investigation of collocations by focusing on the processing of single words or isolated sentences. In contrast, here we analyze EEG brain responses recorded during stimulation with continuous speech, i.e. audio books. We find that the N400 response to collocations is significantly different from that of non-collocations, whereas the effect varies with respect to cortical region (anterior/ posterior) and laterality (left/right). Our results are in line with studies using continuous speech, and they mostly contradict those using artificial paradigms and stimuli. To the best of our knowledge, this is the first neurolinguistic study on collocations using continuous speech stimulation.

neuroscience↗