About 20% of human proteins lack recognized functionalities, and over 40% lack context-specific functionals, underscoring the difficulties of comprehending these proteins and their varied...
A prevailing challenge in genomics still revolves around the comprehension of structural variants, one of which is copy number variation (CNV). To undertake the...
The potential influence of generative models for protein design is drawing the attention of the scientific world. However, there are numerous modalities that mediate...
The field of genomics is ever-changing as a result of an increase in automation and aspects of biological engineering. A groundbreaking study led by...
The availability of biological "big data" and the development of high-throughput sequencing technology have sped up the identification of new protein sequences, making it...
In the quest to create better and faster methods for drug discovery, a team of innovative researchers from various institutions has developed a groundbreaking...
Although molecular dynamics (MD) simulations provide accurate representations of the motion of molecular systems, molecular biology and materials science are challenged by the computational...
AlphaPulldown version 2.0, a noteworthy computational biology program that transforms protein structure modeling, is presented by researchers from the European Molecular Biology Laboratory, Hamburg,...
Gaining insight into the peculiar relationship between the genes we possess and the characteristics they express is undoubtedly one of the most intriguing quests...
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...
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....
As we approach 2025, the integration of artificial intelligence (AI) into bioinformatics is set to transform the field dramatically. Bioinformaticians must stay abreast of...
Artificial Intelligence-powered Virtual Cells (AIVCs) are an exciting new cell-equivalent system. As the name states, AIVCs utilize complex algorithms of artificial intelligence to simulate...
A major field of study is the scientific problem of predicting dynamical mechanisms in proteins after structural revolutions, with molecular dynamics simulations offering important...
The quest to understand biomolecular interactions is central to advancing drug discovery, molecular biology, and bioengineering. A significant step in this journey is accurately...
In genomics, the conventional approach for explaining any gene expression is to cross-analyze bulk RNA sequencing (RNA-seq) data. However, as researchers, more often than...
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