Correction: Synaptic phospholipids as a new target for cortical hyperexcitability and E/I balance in psychiatric disorders.

Following the publication of this article the authors noted that Torfi Sigurdsson's name was misspelled. Instead of Sigrudsson it should be Sigurdsson. The PDF and HTML versions of the paper have been modified accordingly.

Synaptic phospholipids as a new target for cortical hyperexcitability and E/I balance in psychiatric disorders.

Lysophosphatidic acid (LPA) is a synaptic phospholipid, which regulates cortical excitation/inhibition (E/I) balance and controls sensory information processing in mice and man. Altered synaptic LPA signaling was shown to be associated with psychiatric disorders. Here, we show that the LPA-synthesizing enzyme autotaxin (ATX) is expressed in the astrocytic compartment of excitatory synapses and modulates glutamatergic transmission.

Disturbances of novel object exploration and recognition in a chronic ketamine mouse model of schizophrenia.

Schizophrenia is a chronic and devastating disease with an overall lifetime risk of 1%. While positive symptoms of schizophrenia such as hallucinations and delusions are reduced by antipsychotic medication based on the inhibition of type 2 dopaminergic receptors (D2R), negative symptoms (e.g.

MMseqs software suite for fast and deep clustering and searching of large protein sequence sets.

Motivation: Sequence databases are growing fast, challenging existing analysis pipelines. Reducing the redundancy of sequence databases by similarity clustering improves speed and sensitivity of iterative searches. But existing tools cannot efficiently cluster databases of the size of UniProt to 50% maximum pairwise sequence identity or below.

kClust: fast and sensitive clustering of large protein sequence databases.

Background: Fueled by rapid progress in high-throughput sequencing, the size of public sequence databases doubles every two years. Searching the ever larger and more redundant databases is getting increasingly inefficient. Clustering can help to organize sequences into homologous and functionally similar groups and can improve the speed, sensitivity, and readability of homology searches.