Hosna Jabbari

Honey bee (Apis mellifera) gut microbiome associations with viruses and pesticides across Canadian agroecosystems

This study examines how pesticide exposure and RNA virus loadings affect the honey bee gut microbiome across Canadian agroecosystems, identifying consistent bacterial-virus and pesticide-microbe associations.

Comparative Proteomics Across Tissues and Crop Agroecosystems Reveals Agricultural Stressor Responses in the Western Honey Bee

The paper uses tissue-resolved proteomics to analyze how pesticide and pathogen stressors affect honey bee tissues across crop ecosystems, finding stable tissue-specific patterns and crop-associated changes.

CoSTAR: Coarse Stem-Topology Alignment of Pseudoknotted RNA Structures by Relation-Constrained Search

CoSTAR aligns RNA structures by focusing on stems rather than nucleotides, improving alignment of pseudoknotted structures and enabling efficient comparisons across RNA families.

Stable, intronic RNAs explain preservation of introns in Cyanidioschyzon merolae

The paper identifies stable intronic RNAs (sieRNAs) in Cyanidioschizoon merolae that explain the preservation of introns by encoding functional non-coding RNAs involved in stress response and gene regulation.

Structural impact of synonymous mutations in six SARS-CoV-2 Variants of Concern

The paper analyzes synonymous mutations in six SARS-CoV-2 Variants of Concern to assess their impact on RNA secondary structure and stability, finding minimal effects.

Missense mutation knowledge can decrease prediction inaccuracies on protein secondary structure

The paper introduces Mut2Dens, a model that improves protein secondary structure prediction by incorporating missense mutation data, reducing prediction inaccuracies in mutated structures.

Evaluation of network inference algorithms for derivation of metabolic relationships from lipidomic and metabolomic datasets

This study benchmarks network inference algorithms for deriving metabolic relationships from lipidomic and metabolomic data, revealing challenges in interpretation despite some ability to distinguish metabolic states.

Missense mutations: Backbone structure positional effects

The paper evaluates how missense mutations affect protein structure prediction accuracy, finding that current methods overestimate structural changes and struggle with stable mutations and complex proteins.

Markers, Mechanisms and Metrics of Biological Aging: A Scoping Review

This review analyzes 435 biological aging papers to show trends in molecular markers and new metrics, and identifies consistent and conflicting findings.

Tying the Knot: Unraveling the Intricacies of the Coronavirus Frameshift Pseudoknot

The paper predicts energetically favorable secondary structures of coronavirus frameshift elements using hierarchical folding and experimental data, identifying stable motifs and transitions relevant to -1 PRF regulation.

A method to identify high consensus predictions of single-cell metabolic flux

This paper develops a method to identify high consensus predictions of single-cell metabolic flux by comparing two existing tools, Compass and scFEA, and shows they agree on metabolic processes in both healthy and pathological samples.

SparseRNAFolD: Sparse RNA pseudoknot-free Folding including Dangles

SparseRNAFolD improves RNA secondary structure prediction by reducing time and space complexity while including dangles contributions, outperforming LinearFold in memory use and speed for sequences up to 1000 bases.

CParty: Hierarchically Constrained Partition Functionof RNA Pseudoknots

CParty computes a hierarchically constrained partition function for pseudoknotted RNA structures in cubic time, enabling stochastic analysis of pseudoknotted RNA ensembles and revealing kinetic features of SARS-CoV-2 targets.

Prediction of RNA secondary structures in SARS-CoV-2 and comparison with contemporary predictions

The paper predicts RNA secondary structures in SARS-CoV-2 and compares them with existing predictions, finding limited agreement on precise structures but general agreement on structural regions.

Supervised Promoter Recognition: A Benchmark Framework

The paper introduces a benchmark framework for evaluating deep learning models in promoter recognition and finds that current models lack sufficient precision on eukaryotic genomic sequences.

In silico prediction of COVID-19 test efficiency with DinoKnot

This paper predicts how SARS-CoV-2 RNA secondary structure affects qRT-PCR primer efficiency and identifies mutations that may reduce test sensitivity.

SARS-CoV-2 ribosomal frameshifting pseudoknot: Improved secondary structure prediction and detection of inter-viral structural similarity

The paper improves secondary structure prediction of SARS-CoV-2 -1 PRF pseudoknot and identifies structural similarities with SARS-CoV and MERS-CoV pseudoknots.