Terkko Navigator / Bioinformatics (journal)

Asynchronous parallel Bayesian optimization for AI-driven cloud laboratories

Thermodynamic modeling reveals widespread multivalent binding by RNA-binding proteins

Haplotype-based membership inference from summary genomic data

Long reads capture simultaneous enhancer–promoter methylation status for cell-type deconvolution

Investigation of REFINED CNN ensemble learning for anti-cancer drug sensitivity prediction

ISMB/ECCB 2021 proceedings

Expected 10-anonymity of HyperLogLog sketches for federated queries of clinical data repositories

SAILER: scalable and accurate invariant representation learning for single-cell ATAC-seq processing and integration

Comparison of online learning designs during the COVID-19 pandemic within bioinformatics courses in higher education

EnHiC: learning fine-resolution Hi-C contact maps using a generative adversarial framework

KG4SL: knowledge graph neural network for synthetic lethality prediction in human cancers

PathCNN: interpretable convolutional neural networks for survival prediction and pathway analysis applied to glioblastoma

Statistical approaches for differential expression analysis in metatranscriptomics

ISCB Honors 2021 Award Recipients Peer Bork, Barbara Engelhardt, Ben Raphael, Teresa Attwood

doubletD: detecting doublets in single-cell DNA sequencing data

DECODE: a Deep-learning framework for Condensing enhancers and refining boundaries with large-scale functional assays

A novel constrained genetic algorithm-based Boolean network inference method from steady-state gene expression data

Cuttlefish: fast, parallel and low-memory compaction of de Bruijn graphs from large-scale genome collections

Disease gene prediction with privileged information and heteroscedastic dropout

Bayesian information sharing enhances detection of regulatory associations in rare cell types

Constructing small genome graphs via string compression

Umibato: estimation of time-varying microbial interaction using continuous-time regression hidden Markov model

Data-driven speciation tree prior for better species divergence times in calibration-poor molecular phylogenies

Modeling drug combination effects via latent tensor reconstruction

Advancing admixture graph estimation via maximum likelihood network orientation

Metaball skinning of synthetic astroglial morphologies into realistic mesh models for visual analytics and in silico simulations

CentromereArchitect: inference and analysis of the architecture of centromeres

MS2Planner: improved fragmentation spectra coverage in untargeted mass spectrometry by iterative optimized data acquisition

Graph transformation for enzymatic mechanisms

Optimizing blood–brain barrier permeation through deep reinforcement learning for de novo drug design

A variant selection framework for genome graphs

Build a better bootstrap and the RAWR shall beat a random path to your door: phylogenetic support estimation revisited

Weakly supervised learning of RNA modifications from low-resolution epitranscriptome data

JEDI: circular RNA prediction based on junction encoders and deep interaction among splice sites

stPlus: a reference-based method for the accurate enhancement of spatial transcriptomics

Topology-based sparsification of graph annotations

Utilizing image and caption information for biomedical document classification

Real-time mapping of nanopore raw signals

Predicting mechanism of action of novel compounds using compound structure and transcriptomic signature coembedding

CALLR: a semi-supervised cell-type annotation method for single-cell RNA sequencing data

OncoThreads: visualization of large-scale longitudinal cancer molecular data

‘Single-subject studies’-derived analyses unveil altered biomechanisms between very small cohorts: implications for rare diseases

On the feasibility of deep learning applications using raw mass spectrometry data

Predicting MHC-peptide binding affinity by differential boundary tree

CROTON: an automated and variant-aware deep learning framework for predicting CRISPR/Cas9 editing outcomes

Resolving diverse protein–DNA footprints from exonuclease-based ChIP experiments

Model learning to identify systemic regulators of the peripheral circadian clock

Sequence-specific minimizers via polar sets

Practical selection of representative sets of RNA-seq samples using a hierarchical approach

DeepGraphGO: graph neural network for large-scale, multispecies protein function prediction