Related papers: Parallel Protein Community Detection in Large-scal…
Offload of MPI collectives to network devices, e.g., NICs and switches, is being implemented as an effective mechanism to improve application performance by reducing inter- and intra-node communication and bypassing MPI software layers.…
The function of a protein is defined by its interaction partners. Thus, topology-driven network alignment of the protein-protein interaction (PPI) networks of two species should uncover similar interaction patterns and allow identification…
Many networks in nature, society and technology are characterized by a mesoscopic level of organization, with groups of nodes forming tightly connected units, called communities or modules, that are only weakly linked to each other.…
Motivation: Protein-protein interactions (PPI) are critical to the function of proteins in both normal and diseased cells, and many critical protein functions are mediated by interactions.Knowledge of the nature of these interactions is…
Membrane protein classification is a fundamental task in structural bioinformatics, critical to understanding protein functions and accelerating drug discovery. In this study, we propose MP-GCAN, a novel graph-based classification model…
Determining the physicochemical properties of a protein can reveal important insights in their structure, biological functions, stability, and interactions with other molecules. Although tools for computing properties of proteins already…
Community detection and edge prediction are both forms of link mining: they are concerned with discovering the relations between vertices in networks. Some of the vertex similarity measures used in edge prediction are closely related to the…
Multi-scale biomedical knowledge networks are expanding with emerging experimental technologies that generates multi-scale biomedical big data. Link prediction is increasingly used especially in bipartite biomedical networks to identify…
The protein-ligand binding affinity (PLA) prediction goal is to predict whether or not the ligand could bind to a protein sequence. Recently, in PLA prediction, deep learning has received much attention. Two steps are involved in deep…
As the number of solved protein structures increases, the opportunities for meta-analysis of this dataset increase too. Protein structures are known to be formed of domains; structural and functional subunits that are often repeated across…
Proteins are the basic building blocks of life. They usually perform functions by folding to a particular structure. Understanding the folding process could help the researchers to understand the functions of proteins and could also help to…
We present an automated method of identifying communities of functionally related genes from the biomedical literature. These communities encapsulate human gene and protein interactions and identify groups of genes that are complementary in…
Detection of protein-protein interactions (PPIs) plays a vital role in molecular biology. Particularly, infections are caused by the interactions of host and pathogen proteins. It is important to identify host-pathogen interactions (HPIs)…
A fundamental problem in network analysis is clustering the nodes into groups which share a similar connectivity pattern. Existing algorithms for community detection assume the knowledge of the number of clusters or estimate it a priori…
We propose a new local, deterministic and parameter-free algorithm that detects fuzzy and crisp overlapping communities in a weighted network and simultaneously reveals their hierarchy. Using a local fitness function, the algorithm greedily…
Community detection, a fundamental task for network analysis, aims to partition a network into multiple sub-structures to help reveal their latent functions. Community detection has been extensively studied in and broadly applied to many…
The identification of disease-associated genes has recently gathered much attention for uncovering disease complex mechanisms that could lead to new insights into the treatment of diseases. For exploring disease-susceptible genes, not only…
Many real-world networks such as the gene networks, protein-protein interaction networks and metabolic networks exhibit community structures, meaning the existence of groups of densely connected vertices in the networks. Many local…
Many methods have been proposed for community detection in networks, but most of them do not take into account additional information on the nodes that is often available in practice. In this paper, we propose a new joint community…
Protein-Protein Interaction Networks aim to model the interactome, providing a powerful tool for understanding the complex relationships governing cellular processes. These networks have numerous applications, including functional…