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Leveraging permutation testing to assess confidence in positive-unlabeled learning applied to high-dimensional biological datasets
BackgroundCompared to traditional supervised machine learning approaches employing fully labeled samples, positive-unlabeled (PU) learning techniques...
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llperm: a permutation of regressor residuals test for microbiome data
BackgroundDifferential abundance testing is an important aspect of microbiome data analysis, where each taxa is fitted with a statistical test or a...
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Testing environmental effects on taxonomic composition with canonical correspondence analysis: alternative permutation tests are not equal
After applying canonical correspondence analysis to metagenomics data with hugely different library sizes (site totals) it became evident that Canoco...
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Common permutation methods in animal social network analysis do not control for non-independence
The non-independence of social network data is a cause for concern among behavioural ecologists conducting social network analysis. This has led to...
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Circular permutation at azurin’s active site slows down its folding
Circular permutation (CP) is a technique by which the primary sequence of a protein is rearranged to create new termini. The connectivity of the...
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Large-scale lexical and genetic alignment supports a hybrid model of Han Chinese demic and cultural diffusions
The Han Chinese history is shaped by substantial demographic activities and sociocultural transmissions. However, it remains challenging to assess...
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Optimized permutation testing for information theoretic measures of multi-gene interactions
BackgroundPermutation testing is often considered the “gold standard” for multi-test significance analysis, as it is an exact test requiring few...
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Single-sequence protein structure prediction using a language model and deep learning
AlphaFold2 and related computational systems predict protein structure using deep learning and co-evolutionary relationships encoded in multiple...
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Large-scale foundation model on single-cell transcriptomics
Large pretrained models have become foundation models leading to breakthroughs in natural language processing and related fields. Develo**...
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Interaction models matter: an efficient, flexible computational framework for model-specific investigation of epistasis
PurposeEpistasis, the interaction between two or more genes, is integral to the study of genetics and is present throughout nature. Yet, it is seldom...
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The neuroanatomy of developmental language disorder: a systematic review and meta-analysis
Developmental language disorder (DLD) is a common neurodevelopmental disorder with adverse impacts that continue into adulthood. However, its neural...
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ProgPerm: Progressive permutation for a dynamic representation of the robustness of microbiome discoveries
BackgroundIdentification of features is a critical task in microbiome studies that is complicated by the fact that microbial data are high...
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CysPresso: a classification model utilizing deep learning protein representations to predict recombinant expression of cysteine-dense peptides
BackgroundCysteine-dense peptides (CDPs) are an attractive pharmaceutical scaffold that display extreme biochemical properties, low immunogenicity,...
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Conditional permutation importance revisited
BackgroundRandom forest based variable importance measures have become popular tools for assessing the contributions of the predictor variables in a...
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Using protein language models for protein interaction hot spot prediction with limited data
BackgroundProtein language models, inspired by the success of large language models in deciphering human language, have emerged as powerful tools for...
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The cortical representation of language timescales is shared between reading and listening
Language comprehension involves integrating low-level sensory inputs into a hierarchy of increasingly high-level features. Prior work studied brain...
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A Multi-perspective Model for Protein–Ligand-Binding Affinity Prediction
AbstractGathering information from multi-perspective graphs is an essential issue for many applications especially for protein–ligand-binding...
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Rethinking model-based and model-free influences on mental effort and striatal prediction errors
A standard assumption in neuroscience is that low-effort model-free learning is automatic and continuously used, whereas more complex model-based...
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Construction of an ecological model of Sambucus javanica blume in China under different climate scenarios based on maxent model
Sambucus javanica Blume is a Chinese native medicinal plant with high medicinal value. In this study, the MaxEnt model was used to explore the...
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Speech prosody enhances the neural processing of syntax
Human language relies on the correct processing of syntactic information, as it is essential for successful communication between speakers. As an...
