A5004556739- Bioinformatics and Genomic Networks
- Computational Drug Discovery Methods
- Protein Structure and Dynamics
- Microbial Natural Products and Biosynthesis
- Biotin and Related Studies
- Advanced Proteomics Techniques and Applications
- COVID-19 Clinical Research Studies
- Genomics and Phylogenetic Studies
- Machine Learning in Materials Science
- Energy Harvesting in Wireless Networks
- Opportunistic and Delay-Tolerant Networks
- Biomedical Text Mining and Ontologies
- Pharmacological Effects of Natural Compounds
- Genetics, Bioinformatics, and Biomedical Research
- Electrochemical sensors and biosensors
- Energy Efficient Wireless Sensor Networks
- Algal biology and biofuel production
- Cell Image Analysis Techniques
- Ethnobotanical and Medicinal Plants Studies
- Medicinal Plants and Bioactive Compounds
- Microbial Metabolic Engineering and Bioproduction
- Plant biochemistry and biosynthesis
Universidade Federal de Minas Gerais
2014-2022
Universidade de São Paulo
2021-2022
University of California, San Francisco
2019
Universidade Federal de Lavras
2014
Machine learning-based drug discovery success depends on molecular representation. Yet traditional fingerprints omit both the protein and pointers back to structural information that would enable better model interpretability. Therefore, we propose LUNA, a Python 3 toolkit calculates encodes protein–ligand interactions into new hashed inspired by Extended Connectivity FingerPrint (ECFP): EIFP (Extended Interaction FingerPrint), FIFP (Functional Hybrid (HIFP). LUNA also provides visual...
Essential roles in biological systems depend on protein-ligand recognition, which is mostly driven by specific non-covalent interactions. Consequently, investigating these interactions contributes to understanding how molecular recognition occurs. Nowadays, a large-scale data set of complexes available the Protein Data Bank, what led several tools be proposed as an effort elucidate Nonetheless, there not all-in-one tool that couples statistical, visual, and interactive analysis conserved...
Evolutionarily related proteins can present similar structures but very dissimilar sequences. Hence, understanding the role of inter-residues contacts for protein structure has been target many studies. Contacts comprise non-covalent interactions, which are essential to stabilize macromolecular such as proteins. Here we show VTR, a new method detection analogous in pairs. The VTR web tool performs structural alignment between and detects interactions that occur regions. To evaluate our tool,...
Abstract Machine learning-based drug discovery success depends on molecular representation. Yet traditional fingerprints omit both the protein and pointers back to structural information that would enable better model interpretability. Therefore, we propose LUNA, a Python 3 toolkit calculates encodes protein-ligand interactions into new hashed inspired by Extended Connectivity Finger-Print (ECFP): EIFP (Extended Interaction FingerPrint), FIFP (Functional Hybrid FingerPrint (HIFP). LUNA also...
A huge amount of data about genomes and sequence variation is available continues to grow on a large scale, which makes experimentally characterizing these mutations infeasible regarding disease association effects protein structure function. Therefore, reliable computational approaches are needed support the understanding their impacts. Here, we present VERMONT 2.0, visual interactive platform that combines structural parameters with visualizations make impact point more understandable. We...
In this paper, we propose an interactive visualization called VERMONT which tackles the problem of visualizing mutations and infers their possible effects on conservation physicochemical topological properties in protein families. More specifically, visualize a set structure-based sequence alignments integrate several structural parameters that should aid biologists gaining insight into consequences mutations. allowed us to identify patterns position-specific as well exceptions may help...
Interactions between proteins and ligands are relevant in many biological processes. In the last years, such interactions have gained even more attention as comprehension of protein-ligand molecular recognition is an important step to ligand prediction, target identificantion, drug design, among others. This article presents GReMLIN (Graph Mining strategy infer protein-Ligand INteraction patterns), a search for conserved set related proteins, based on frequent subgraph mining, that able...
Interactions between proteins and non-proteic small molecule ligands play important roles in the biological processes of living systems. Thus, development computational methods to support our understanding ligand-receptor recognition process is fundamental importance since these are a major step towards ligand prediction, target identification, lead discovery, more. This article presents visGReMLIN, web server that couples graph mining-based strategy detect motifs at protein-ligand interface...
Protein-ligand interaction (PLI) networks show how proteins interact with small non-protein ligands through noncovalent bonding. Understanding such interactions is a crucial step towards ligand prediction, target identification and drug design. We propose CALI (Complex network-based Analysis of protein-Ligand Interactions), graph-based, visual strategy coupled complex network topological properties to summarize detect frequent patterns in PLIs. Patterns obtained were compared experimentally...
Abstract Evolutionarily related proteins can present similar structures but very dissimilar sequences. Hence, understanding the role of inter-residues contacts for protein structure has been target many studies. Contacts comprise non-covalent interactions, which are essential to stabilize macromolecular such as proteins. Here we show VTR, a new method detection analogous in pairs. VTR performs structural alignment between and detects interactions that occur regions. To evaluate our tool,...
This paper presents GB-MAC, an asynchronous cross-layer medium access control protocol. Several MAC protocols suffer from the sleep-delay problem which causes a large latency in multi-hop communications. In our approach, we create backbone composed by nodes with short active-sleep cycles to ensure fast relay of messages and sink node. About 15% are recruited form backbone. Moreover, protocol is order avoid complexity arising constant time synchronizations. Simulations have shown that low all...
Abstract PhycoMine is data warehouse system created to fostering the analysis of complex and integrated from microalgae species in a single computational environment. The was developed on top InterMine software system, it has implemented an extended database model, containing series tools that help users mining individual group data. platform widgets facilitate simultaneous different datasets. Among PhycoMine, there are options for chromosome distribution, gene expression variation via...
Abstract Background A huge amount of data about genomes and sequence variation is available continues to grow on a large scale, which makes experimentally characterizing these mutations infeasible regarding disease association effects protein structure function. Therefore, reliable computational approaches are needed support the understanding their impacts. Here, we present VERMONT 2.0, visual interactive platform that combines structural parameters with visualizations make impact point more...
Abstract Evolutionarily related proteins can present similar structures but very dissimilar sequences. Hence, understanding the role of inter-residues contacts for protein structure has been target many studies. Contacts comprise non-covalent interactions, which are essential to stabilize macromolecular such as proteins. Here we show VTR, a new method detection analogous in pairs. VTR performs structural alignment between and detects interactions that occur regions. To evaluate our tool,...