Biology subjects

Hernandez Sanchez, L. F.

Publications and source records attributed to Hernandez Sanchez, L. F..

3 recordsLinked to original sources

bioRxiv2022

Extending protein interaction networks using proteoforms and small molecules

Biological network analysis is used to interpret modern high-throughput biomedical data sets in terms of biological functions and pathways. However, the results greatly depend on the topological characteristics of the underlying network, commonly composed of nodes representing genes or proteins that are connected by edges when interacting. In this study, we build biological networks accounting for small molecules, protein isoforms and post-translational modifications. We highlight how these change the global structure of the network and how the connectedness of pathway-based networks is altered. Our findings highlight the importance of carefully crafting the networks for network analysis to better represent the reality of biological systems.

bioinformatics↗

bioRxiv2018

PathwayMatcher: multi-omics pathway mapping and proteoform network generation

BackgroundMapping biomedical data to functional knowledge is an essential task in bioinformatics and can be achieved by querying identifiers, e.g. gene sets, in pathway knowledgebases. However, the isoform and post-translational modification states of proteins are lost when converting input and pathways into gene-centric lists.\n\nFindingsBased on the Reactome knowledgebase, we built a network of protein-protein interactions accounting for the documented isoform and modification statuses of proteins. We then implemented a command line application called PathwayMatcher (github.com/PathwayAnalysisPlatform/PathwayMatcher) to query this network. PathwayMatcher supports multiple types of omics data as input, and outputs the possibly affected biochemical reactions, subnetworks, and pathways.\n\nConclusionsPathwayMatcher enables refining the network-representation of pathways by including isoform and post-translational modifications. The specificity of pathway analyses is hence adapted to different levels of granularity and it becomes possible to distinguish interactions between different forms of the same protein.

bioinformatics↗

bioRxiv2018

Analysing the structure of pathways and its influence on the interpretation of biomedical datasets

Biochemical pathways are commonly used as a reference to conduct functional analysis on biomedical omics datasets, where experimental results are mapped to knowledgebases comprising known molecular interactions collected from the literature. Due to their central role, the content of the functional knowledgebases directly influences the outcome of pathway analyses. In this study, we investigate the structure of the current pathway knowledge, as exemplified by Reactome, discuss the consequences for biological interpretation, and outline possible improvements in the use of pathway knowledgebases. By providing a view of the underlying network structure, we aim to help pathway analysis users manage their expectations and better identify possible artefacts in the results.

bioinformatics↗