Studies in health technology and informatics
Nov 23, 2023
Recombinant protein expression is a crucial technique in biology, with E. coli being the most widely used expression system. However, due to growth pressure, the expression of large molecular weight proteins in E. coli has remained a challenging task...
Pakistan journal of pharmaceutical sciences
Nov 1, 2023
Scutellaria sibthorpii is used in treatment of bacterial infections, pains and inflammations. The leaf was extracted by maceration and then partitioned with hexane, ethyl acetate and n-butanol. The extract was screened for phytochemicals. The antioxi...
Transcriptomic data is accumulating rapidly; thus, scalable methods for extracting knowledge from this data are critical. Here, we assembled a top-down expression and regulation knowledge base for Escherichia coli. The expression component is a 1035-...
It has been known for decades that codon usage contributes to translation efficiency and hence to protein production levels. However, its role in protein synthesis is still only partly understood. This lack of understanding hampers the design of synt...
MOTIVATION: DNA methylation plays a key role in a variety of biological processes. Recently, Nanopore long-read sequencing has enabled direct detection of these modifications. As a consequence, a range of computational methods have been developed to ...
MOTIVATION: Applications in synthetic and systems biology can benefit from measuring whole-cell response to biochemical perturbations. Execution of experiments to cover all possible combinations of perturbations is infeasible. In this paper, we prese...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2022
The ability to manipulate capripoxvirus through gene knockouts and gene insertions has become an increasingly valuable research tool in elucidating the function of individual genes of capripoxvirus, as well as in the development of capripoxvirus-base...
Journal of computational biology : a journal of computational molecular cell biology
Jan 1, 2022
We propose GRNUlar, a novel deep learning framework for supervised learning of gene regulatory networks (GRNs) from single-cell RNA-Sequencing (scRNA-Seq) data. Our framework incorporates two intertwined models. First, we leverage the expressive abil...
The effectiveness of deep learning methods can be largely attributed to the automated extraction of relevant features from raw data. In the field of functional genomics, this generally concerns the automatic selection of relevant nucleotide motifs fr...
Interactions between proteins and small molecule metabolites play vital roles in regulating protein functions and controlling various cellular processes. The activities of metabolic enzymes, transcription factors, transporters and membrane receptors ...
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