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Protein retrieval, which targets the deconstruction of the relationship between sequences, structures and functions, empowers the advancing of biology. Basic Local Alignment Search Tool (BLAST), a sequence-similarity-based algorithm, has…
We study the problem of efficiently clustering protein sequences in a limited information setting. We assume that we do not know the distances between the sequences in advance, and must query them during the execution of the algorithm. Our…
With the exponential increase of the protein sequence databases over time, multiple-sequence alignment (MSA) methods, like PSI-BLAST, perform exhaustive and time-consuming database search to retrieve evolutionary information. The resulting…
Numerous machine learning (ML) models employed in protein function and structure prediction depend on evolutionary information, which is captured through multiple-sequence alignments (MSA) or position-specific scoring matrices (PSSM) as…
Protein motifs are conserved fragments occurred frequently in protein sequences. They have significant functions, such as active site of an enzyme. Search and clustering protein sequence motifs are computational intensive. Most existing…
Protein sequence analysis underpins research in biophysics, computational biology, and bioinformatics. We introduce BEER, a crossplatform graphical interface that accepts FASTA or Protein Data Bank (PDB) files, or manual sequence entry, and…
Artificial intelligence (AI) tools are gaining more and more ground each year in bioinformatics. Learning algorithms can be taught easily by using the existing enormous biological databases, and the resulting models can be used for the…
The Basic Local Alignment Search Tool (BLAST) is currently the most popular method for searching databases of biological sequences. BLAST compares sequences via similarity defined by a weighted edit distance, which results in it being…
Identifying similar protein sequences is a core step in many computational biology pipelines such as detection of homologous protein sequences, generation of similarity protein graphs for downstream analysis, functional annotation and gene…
Protein analysis tasks arising in healthcare settings often require accurate reasoning under protein sequence constraints, involving tasks such as functional interpretation of disease-related variants, protein-level analysis for clinical…
Metagenomics is the study of environments through genetic sampling of their microbiota. Metagenomic studies produce large datasets that are estimated to grow at a faster rate than the available computational capacity. A key step in the…
Predicting the subcellular localization of proteins is an important and challenging problem. Traditional experimental approaches are often expensive and time-consuming. Consequently, a growing number of research efforts employ a series of…
AI assistants can now carry out tasks for users by directly interacting with website UIs. Current semantic parsing and slot-filling techniques cannot flexibly adapt to many different websites without being constantly re-trained. We propose…
The identification of bitter peptides is crucial in various domains, including food science, drug discovery, and biochemical research. These peptides not only contribute to the undesirable taste of hydrolyzed proteins but also play key…
Protein representation learning is a challenging task that aims to capture the structure and function of proteins from their amino acid sequences. Previous methods largely ignored the fact that not all amino acids are equally important for…
This report presents the implementation of a protein sequence comparison algorithm specifically designed for speeding up time consuming part on parallel hardware such as SSE instructions, multicore architectures or graphic boards. Three…
Decoding protein-protein interactions (PPIs) at the residue level is crucial for understanding cellular mechanisms and developing targeted therapeutics. We present Seq2Bind Webserver, a computational framework that leverages fine-tuned…
Protein Fragment Motif Finder (PFMFind) is a system that enables efficient discovery of relationships between short fragments of protein sequences using similarity search. It supports queries based on score matrices and PSSMs obtained…
SMISS is a novel web server for protein function prediction. Three different predictors can be selected for different usage. It integrates different sources to improve the protein function prediction accuracy, including the query protein…
Most of the web user's requirements are search or navigation time and getting correctly matched result. These constrains can be satisfied with some additional modules attached to the existing search engines and web servers. This paper…