With its recent advancements, scRNA sequencing has enabled scientists to view the biological world at the most local of levels- the single cell. Thanks...
Integrating metabolomics with other omics and providing insights into the biology of disease requires bioinformatics competence. Integration is difficult with present approaches, though, as...
Although RNA 3D structures are important in understanding their functions and in the design of new drugs, their accurate prediction is still a challenge....
RNAs are crucial molecules that convey genetic information necessary for life, and they have a big impact on biotechnology and medicine development. However, the...
The DNA sequences of all living organisms hold the fundamental instructions for life. Massive datasets of entire genomes, together with machine learning advancements, may...
Protein engineering heavily relies on generating sequences using computational models. Limitations such as lack of benchmarking opportunities, scarcity of large protein function datasets, and...
In the fast-paced world of drug discovery, one of the most crucial aspects is understanding protein-ligand interactions. With the correct algorithms for predicting protein-ligand...
It has been demonstrated that there is a functional correlation between transcriptional activity, thermodynamic stability, DNA breathing, and transcription factor (TF) binds. The researchers...
A groundbreaking new research from the University of Georgia unveils that omega-3 and omega-6 fatty acids may play an integral role in cancer prevention,...
In an era where biological data grows exponentially, bioinformatics has emerged as a vital interdisciplinary field that combines biology, computer science, mathematics, and statistics....
Computational pathology is the evolution of cancer diagnosis into a new era, with the application of artificial intelligence to understand complex histopathology images. Generally,...
For drug development to be effective, it is essential to accurately predict the various bound-state conformations of small compounds, especially in situations where intricate...
In a significant move for the scientific community, Google DeepMind has finally released the open-source code for AlphaFold3, their groundbreaking protein structure prediction tool....
As biologists have noticed, evolution has modified both bacteria and bacteriophages (i.e., viruses of bacteria), making them more complex on a smile's molecular level....
Virtual screening techniques, which concentrate on binding affinities, are becoming more and more popular for early-stage drug development. Although deep learning-based methods predict binding...
The identification and comprehension of the mechanisms of potential drug compounds is a complex and expensive endeavor in the constantly changing pharmaceutical research landscape....
Large-scale screening techniques that are resource-intensive and offer limited control on binding mode are usually used to produce macrocyclic binders to therapeutic proteins. There...
The emergence of Protein Language Models (PLMs) is changing biological research for the better through efficient prediction of functional annotations and protein structures. However,...
Recombinant proteins must be stable in order to be used in biotechnological or medicinal applications. Both the creation of new proteins and the stabilization...
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