A5090706824- Genomics and Phylogenetic Studies
- Gut microbiota and health
- Microbial Community Ecology and Physiology
- RNA and protein synthesis mechanisms
- Machine Learning in Bioinformatics
- Genomics and Rare Diseases
- Bioinformatics and Genomic Networks
- Neural Networks and Applications
- Chemistry and Stereochemistry Studies
- Computational Drug Discovery Methods
- Genetic Associations and Epidemiology
- Electrochemical Analysis and Applications
- Medical Imaging Techniques and Applications
- Epigenetics and DNA Methylation
- Nuclear Physics and Applications
- Chemical Reactions and Isotopes
- Laser-induced spectroscopy and plasma
- Radiomics and Machine Learning in Medical Imaging
- Microbial Natural Products and Biosynthesis
- Photosynthetic Processes and Mechanisms
- Indoor Air Quality and Microbial Exposure
- Mass Spectrometry Techniques and Applications
- Glycosylation and Glycoproteins Research
- Cold Fusion and Nuclear Reactions
- Space Exploration and Technology
Pacific Northwest National Laboratory
2024-2025
Rutgers, The State University of New Jersey
2016-2023
Technical University of Munich
2013-2019
Institute for Advanced Study
2016-2018
Automated annotation of protein function is challenging. As the number sequenced genomes rapidly grows, overwhelming majority products can only be annotated computationally. If computational predictions are to relied upon, it crucial that accuracy these methods high. Here we report results from first large-scale community-based critical assessment (CAFA) experiment. Fifty-four representing state art for prediction were evaluated on a target set 866 proteins 11 organisms. Two findings stand...
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Any method that de novo predicts protein function should do better than random. More challenging, it also ought to outperform simple homology-based inference.Here, we describe a few methods predict exclusively through homology. Together, they set the bar or lower limit for future improvements.During development of these methods, faced two surprises. Firstly, our most successful implementation baseline ranked very high at CAFA1. In fact, best combination fared only slightly worse...
Abstract Motivation The rapid drop in sequencing costs has produced many more (predicted) protein sequences than can feasibly be functionally annotated with wet-lab experiments. Thus, computational methods have been developed for this purpose. Most of these employ homology-based inference, approximated via sequence alignments, to transfer functional annotations between proteins. increase the number available sequences, however, drastically increased search space, thus significantly slowing...
Abstract The rise of targeted therapies for cancer treatment has fueled the development algorithms that take molecular profile (e.g. mutations, transcripts, etc.) a tumor and predict effect drug on this tumor. Recent advancements in deep learning have enabled prediction cell’s response to untested, potentially novel drugs using measurements [1]. To assess clinical reliability these algorithms, we first need measure their performance across range data model systems cell lines, organoids,...
Any two unrelated individuals differ by about 10,000 single amino acid variants (SAVs). Do these impact molecular function? Experimental answers cannot answer comprehensively, while state-of-the-art prediction methods can. We predicted the functional impacts of SAVs within human and for between other species. Several surprising results stood out. Firstly, four (CADD, PolyPhen-2, SIFT, SNAP2) agreed 10 percentage points on rare with effect. However, they differed substantially common SAVs:...
Microbial functional diversification is driven by environmental factors, i.e. microorganisms inhabiting the same niche tend to be more functionally similar than those from different environments. In some cases, even closely phylogenetically related microbes differ across environments taxa. While microbial similarities are often reported in terms of taxonomic relationships, no existing databases directly link functions environment. We previously developed a method for comparing on basis...
Developments in experimental and computational biology are advancing our understanding of how protein sequence variation impacts molecular function. However, the leap from micro level function to macro whole organism, e.g. disease, remains barred. Here, we present new results emphasizing earlier work that suggested some links disease. We focused on non-synonymous single nucleotide variants, also referred as amino acid variants (SAVs). Building upon OMIA (Online Mendelian Inheritance...
Determining the repertoire of a microbe's molecular functions is central question in microbial biology. Modern techniques achieve this goal by comparing genetic material against reference databases functionally annotated genes/proteins or known taxonomic markers such as 16S rRNA. Here, we describe novel approach to exploring bacterial functional repertoires without databases. Our Fusion scheme establishes relationships between bacteria and assigns organisms Fusion-taxa that differ from...
Abstract Background Accumulating evidence suggests that the human microbiome impacts individual and public health. City subway systems are human-dense environments, where passengers often exchange microbes. The MetaSUB project participants collected samples from surfaces in different cities performed metagenomic sequencing. Previous studies focused on taxonomic composition of these microbiomes no explicit functional analysis had been done till now. Results As a part 2018 CAMDA challenge, we...
The past two decades of analytical efforts have highlighted how much more remains to be learned about the human genome and, particularly, its complex involvement in promoting disease development and progression. While numerous computational tools exist for assessment functional pathogenic effects variants, their precision is far from satisfactory, particularly clinical use. Accumulating evidence also suggests that microbiome's interaction with plays a critical role determining health states....
Non-synonymous Single Nucleotide Variants (nsSNVs), resulting in single amino acid variants (SAVs), are important drivers of evolutionary adaptation across the tree life. Humans carry on average over 10,000 SAVs per individual genome, many which likely have little to no impact function protein they affect. Experimental evidence for changes as a result remain sparse – situation that can be somewhat alleviated by predicting their using computational methods. Here, we used SNAP examine both...
ABSTRACT Determining the repertoire of a microbe’s molecular functions is central question in microbial biology. Modern techniques achieve this goal by comparing genetic material against reference databases functionally annotated genes/proteins or known taxonomic markers such as 16S rRNA. Here we describe novel approach to exploring bacterial functional repertoires without databases. Our Fusion scheme establishes relationships between bacteria and assigns organisms Fusion-taxa that differ...
Abstract Single nucleotide variants (SNVs) have been widely studied in the past due to being main source of human genetic variation. Less is known about effect single amino acid (SAVs) immense resources required for comprehensive experimental studies. In contrast, silico methods predicting effects sequence upon molecular function and organism are readily available contributed unexpected suggestions, e.g. that SAVs common a population (shared by >5% population) have, on average, more...
Abstract Microbial functional diversification is driven by environmental factors, i.e. microorganisms inhabiting the same niche tend to be more functionally similar than those from different environments. In some cases, even closely phylogenetically related microbes differ across environments taxa. While microbial similarities are often reported in terms of taxonomic relationships, no existing databases directly links functions environment. We previously developed a method for comparing on...