A5028126983- Computational Drug Discovery Methods
- Bioinformatics and Genomic Networks
- Protein Structure and Dynamics
- Microbial Metabolic Engineering and Bioproduction
- Microbial Natural Products and Biosynthesis
- Enzyme Structure and Function
- Machine Learning in Bioinformatics
- SARS-CoV-2 and COVID-19 Research
- Pharmacogenetics and Drug Metabolism
- Gene expression and cancer classification
- Synthesis and biological activity
- Viral Infectious Diseases and Gene Expression in Insects
- RNA and protein synthesis mechanisms
- COVID-19 Clinical Research Studies
- Gene Regulatory Network Analysis
- Metabolomics and Mass Spectrometry Studies
- Evolutionary Algorithms and Applications
- Genetics, Bioinformatics, and Biomedical Research
- Aquatic Ecosystems and Phytoplankton Dynamics
- Endoplasmic Reticulum Stress and Disease
- Pharmacological Effects and Assays
- Neural Networks and Applications
- Chemical Reactions and Isotopes
- Biomedical Text Mining and Ontologies
- Genomics and Phylogenetic Studies
Institute for Research in Biomedicine
2018-2023
Universitat Politècnica de Catalunya
2018-2022
University of Basel
2013-2019
SIB Swiss Institute of Bioinformatics
2014-2018
University of Milano-Bicocca
2012
Homology modelling has matured into an important technique in structural biology, significantly contributing to narrowing the gap between known protein sequences and experimentally determined structures. Fully automated workflows servers simplify streamline homology process, also allowing users without a specific computational expertise generate reliable models have easy access results, their visualization interpretation. Here, we present update SWISS-MODEL server, which pioneered field of...
Protein structure homology modelling has become a routine technique to generate 3D models for proteins when experimental structures are not available. Fully automated servers such as SWISS-MODEL with user-friendly web interfaces reliable without the need complex software packages or downloading large databases. Here, we describe latest version of expert system protein modelling. The template library provides annotation quaternary and essential ligands co-factors allow building complete...
Cellular processes often depend on interactions between proteins and the formation of macromolecular complexes. The impairment such can lead to deregulation pathways resulting in disease states, it is hence crucial gain insights into nature assemblies. Detailed structural knowledge about complexes protein-protein growing, but experimentally determined three-dimensional multimeric assemblies are outnumbered by supported non-structural experimental evidence. Here, we aim fill this gap modeling...
Every second year, the community experiment "Critical Assessment of Techniques for Structure Prediction" (CASP) is conducting an independent blind assessment structure prediction methods, providing a framework comparing performance different approaches and discussing latest developments in field. Yet, developers automated computational modeling methods clearly benefit from more frequent evaluations based on larger sets data. The "Continuous Automated Model EvaluatiOn (CAMEO)" platform...
Abstract Chemical descriptors encode the physicochemical and structural properties of small molecules, they are at core chemoinformatics. The broad release bioactivity data has prompted enriched representations compounds, reaching beyond chemical structures capturing their known biological properties. Unfortunately, not available for most which limits applicability to a few thousand well characterized compounds. Here we present collection deep neural networks able infer signatures any...
The Columbia Cancer Target Discovery and Development (CTD2) Center is developing PANACEA, a resource comprising dose-responses RNA sequencing (RNA-seq) profiles of 25 cell lines perturbed with ∼400 clinical oncology drugs, to study tumor-specific drug mechanism action. Here, this serves as the basis for DREAM Challenge assessing accuracy sensitivity computational algorithms de novo polypharmacology predictions. Dose-response perturbational 32 kinase inhibitors are provided 21 teams who blind...
Biomedical data is accumulating at a fast pace and integrating it into unified framework major challenge, so that multiple views of given biological event can be considered simultaneously. Here we present the Bioteque, resource unprecedented size scope contains pre-calculated biomedical descriptors derived from gigantic knowledge graph, displaying more than 450 thousand entities 30 million relationships between them. The Bioteque integrates, harmonizes, formats collected over 150 sources,...
Abstract We present the results of first independent assessment protein assemblies in CASP. A total 1624 oligomeric models were submitted by 108 predictor groups for 30 targets CASP12 edition. evaluated accuracy predictions comparison to their reference structures at interface patch and residue contact levels. find that patches are more reliably predicted than specific contacts. Whereas none 15 hard have successful contacts interface, six with resemblance patch. Successful exist all suitable...
Abstract Critical blind assessment of structure prediction techniques is crucial for the scientific community to establish state art, identify bottlenecks, and guide future developments. In Assessment Techniques in Structure Prediction (CASP), human experts assess performance participating methods relation difficulty task a biennial experiment on approximately 100 targets. Yet, development automated computational modeling requires more frequent evaluation cycles larger sets data. The...
Biological data is accumulating at an unprecedented rate, escalating the role of data‐driven methods in computational drug discovery. This scenario favored by recent advances machine learning algorithms, which are optimized for huge datasets and consistently beat predictive performance previous art, rapidly approaching human expert reasoning. The urge to couple biological cutting‐edge has spurred developments integration knowledge representation, especially form heterogeneous, multiplex...
SUMMARY The Columbia Cancer Target Discovery and Development (CTD 2 ) Center has developed PANACEA (PANcancer Analysis of Chemical Entity Activity), a collection dose-response curves perturbational profiles for 400 clinical oncology drugs in cell lines selected to optimally represent 19 cancer subtypes. This resource, study tumor-specific drug mechanism action, was instrumental hosting DREAM Challenge assess computational models de novo polypharmacology prediction. Dose-response 32 kinase...
Abstract We present the Chemical Checker (CC), a resource that provides processed, harmonized and integrated bioactivity data on 800,000 small molecules. The CC divides into five levels of increasing complexity, ranging from chemical properties compounds to their clinical outcomes. In between, it considers targets, off-targets, perturbed biological networks several cell-based assays such as gene expression, growth inhibition morphological profilings. CC, are expressed in vector format, which...
<p>Limnologists have long recognized that one of the goals their discipline is to increase its predictive capability. In recent years, role prediction in applied ecology escalated, mainly due man’s increased ability change biosphere. Such alterations often came with unplanned and noticeably negative side effects mushrooming from lack proper attention long-term consequences. Regression analysis common limnological parameters has been successfully develop models relating variability...
Abstract Chemical descriptors encode the physicochemical and structural properties of small molecules, they are at core chemoinformatics. The broad release bioactivity data has prompted enriched representations compounds, reaching beyond chemical structures capturing their known biological properties. Unfortunately, ‘bioactivity descriptors’ not available for most which limits applicability to a few thousand well characterized compounds. Here we present collection deep neural networks able...
Until a vaccine becomes available, the current repertoire of drugs is our only therapeutic asset to fight SARS-CoV-2 outbreak. Indeed, emergency clinical trials have been launched assess effectiveness many marketed drugs, tackling decrease viral load through several mechanisms. Here, we present an online resource, based on small-molecule bioactivity signatures and natural language processing, expand portfolio compounds with potential treat COVID-19. By comparing set reported be potentially...
The Columbia Cancer Target Discovery and Development (CTD2) Center has developed PANACEA (PANcancer Analysis of Chemical Entity Activity), a collection dose-response curves perturbational profiles for 400 clinical oncology drugs in cell lines selected to optimally represent 19 cancer subtypes. This resource, study tumor-specific drug mechanism action, was instrumental hosting DREAM Challenge assess computational models de novo polypharmacology prediction. Dose-response 32 kinase inhibitors...
We present an online resource, based on small-molecule bioactivity signatures and natural language processing, to expand the portfolio of compounds with potential treat COVID-19. By comparing set drugs reported be potentially active against SARS-CoV-2 a universe 1M bioactive molecules, we identify that display analogous chemical functional features current COVID-19 candidates. Searches can filtered by level evidence mechanism action, results restricted drug molecules or include much broader...
We present an online resource, based on small-molecule bioactivity signatures and natural language processing, to expand the portfolio of compounds with potential treat COVID-19. By comparing set drugs reported be potentially active against SARS-CoV-2 a universe 1M bioactive molecules, we identify that display analogous chemical functional features current COVID-19 candidates. Searches can filtered by level evidence mechanism action, results restricted drug molecules or include much broader...