MINNO: An Open Source Software for Refining Metabolic Networks and Investigating Complex Network Activity Using Empirical Metabolomics Data.

Metabolomics is a powerful tool for uncovering biochemical diversity in a wide range of organisms. Metabolic network modeling is commonly used to frame metabolomics data in the context of a broader biological system. However, network modeling of poorly characterized nonmodel organisms remains challenging due to gene homology mismatches which lead to network architecture errors.

Metabolic Interactive Nodular Network for Omics (MINNO): Refining and investigating metabolic networks based on empirical metabolomics data.

Metabolomics is a powerful tool for uncovering biochemical diversity in a wide range of organisms, and metabolic network modeling is commonly used to frame results in the context of a broader homeostatic system. However, network modeling of poorly characterized, non-model organisms remains challenging due to gene homology mismatches. To address this challenge, we developed Metabolic Interactive Nodular Network for Omics (MINNO), a web-based mapping tool that takes in empirical metabolomics data to refine metabolic networks for both model and unusual organisms.

A biochemical mechanism for time-encoding memory formation within individual synapses of Purkinje cells.

Within the classical eye-blink conditioning, Purkinje cells within the cerebellum are known to suppress their tonic firing rates for a well defined time period in response to the conditional stimulus after training. The temporal profile of the drop in tonic firing rate, i.e.

Production of L-phenylacetyl carbinol by immobilized cells of Saccharomyces cerevisiae.

Conversion of benzaldehyde to L-phenylacetyl carbinol (L-PAC) was achieved with immobilized, growing cells of Saccharomyces cerevisiae in different reactors. Product formation increased (31%) with the subsequent initial reuses of the entrapped cells. Biomass production and PAC formation depleted (40 and 57%, respectively) after 4-5 continuous growth and biotransformation cycles.

Microbial transformation of 13-ethyl-3-methoxy-8,14-seco-gona-1,3,5(10),9(11)-tetraene-14, 17-dione to its 17-beta hydroxy derivative by Pichia farinosa in pilot plant fermentors.

Parameters for microbial transformation of 13-ethyl-3-methoxy-8, 14-seco-gona-1,3,5 (10), 9(11)-tetraene-14,17-dione to its 17 beta-hydroxy derivative by P. farinosa have been standardised in pilot plant fermentors. The yield of the pure crystalline compound was 80%.