A generic diffusion-based approach for 3D human pose prediction in the wild

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Teaching and learning support for bioinformatics has become a popular research area. Proteomics education can be bridged with technology enhancements such that tool support for protein structures experiments. Generally, students in proteomics require diffe ...

Background: Protein variability can now be studied by measuring high-resolution tolerance-to-substitution maps and fitness landscapes in saturated mutational libraries. But these rich and expensive datasets are typically interpreted coarsely, restricting d ...

Despite the increasing popularity of massive open online courses (MOOCs), many suffer from high dropout and low success rates. Early prediction of student success for targeted intervention is therefore essential to ensure no student is left behind in a cou ...

Amongst the substances found in any living organism one of the most central in the workings of each living cell is deoxyribonucleic acid (DNA). For that reason it has been the subject of research in many of its aspects. These range from DNA sequencing to a ...

The growing adoption of point clouds as an imaging modality has stimulated the search for efficient solutions for compression. Learning-based algorithms have been reporting increasingly better performance and are drawing the attention from the research com ...

Self-supervised neural language models with attention have recently been applied to biological sequence data, advancing structure, function and mutational effect prediction. Some protein language models, including MSA Transformer and AlphaFold's EvoFormer, ...

The need for interfacing structural biology and biophysics to molecular evolution is being increasingly recognized. One part of the big problem is to understand how physics and chemistry shape the sequence space available to functional proteins, while sati ...

Simultaneous prediction of wrist and hand motions is essential for the natural interaction with hand prostheses. In this paper, we propose a novel multi-out Gaussian process (MOGP) model and a multi-task deep learning (MTDL) algorithm to achieve simultaneo ...

cgDNA is a package for the prediction of sequence-dependent configuration-space free energies for B-form DNA at the coarse-grain level of rigid bases. For a fragment of any given length and sequence, cgDNA calculates the configuration of the associated fre ...

Despite the structural and functional information contained in the statistical coupling between pairs of residues in a protein, coevolution associated with function is often obscured by artifactual signals such as genetic drift, which shapes a protein's ph ...

Numerical simulation of parametrized differential equations is of crucial importance in the study of real-world phenomena in applied science and engineering. Computational methods for real-time and many-query simulation of such problems often require prohi ...

We introduce a generic convex energy functional that is suitable for both grayscale and vector-valued images. Our functional is based on the eigenvalues of the structure tensor, therefore it penalizes image variation at every point by taking into account t ...

Image Processing problems are notoriously difficult. To name a few of these difficulties, they are usually ill-posed, involve a huge number of unknowns (from one to several per pixel!), and images cannot be considered as the linear superposition of a few p ...

Recent breakthroughs in deep learning often rely on representation learning and knowledge transfer. In recent years, unsupervised and self-supervised techniques for learning speech representation were developed to foster automatic speech recognition. Up to ...

Predicting the effects of mutations on protein stability is a key problem in fundamental and applied biology, still unsolved even for the relatively simple case of small, soluble, globular, monomeric, two-state-folder proteins. Many articles discuss the li ...

A generic diffusion-based approach for 3D human pose prediction in the wild

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Enhanced Student Learning in Proteomics - an Interactive Tool Support for Teaching Workflows

Detection and sequence/structure mapping of biophysical constraints to protein variation in saturated mutational libraries and protein sequence alignments with a dedicated server

Meta Transfer Learning for Early Success Prediction in MOOCs

Computation and Visualization in Multiscale Modelling of DNA Mechanics

Latent Space Slicing for Enhanced Entropy Modeling in Learning-Based Point Cloud Geometry Compression

Protein language models trained on multiple sequence alignments learn phylogenetic relationships

How Structural and Physicochemical Determinants Shape Sequence Constraints in a Functional Enzyme

Simultaneous Prediction of Wrist and Hand Motions via Wearable Ultrasound Sensing for Natural Control of Hand Prostheses

cgDNA: a software package for the prediction of sequence-dependent coarse-grain free energies of B-form DNA

Extracting phylogenetic dimensions of coevolution reveals hidden functional signals

Reduced basis methods for time-dependent problems

Convex Generalizations of Total Variation Based on the Structure Tensor with Applications to Inverse Problems

Patch-based methods for variational image processing problems

Word-level Embeddings for Cross-Task Transfer Learning in Speech Processing

Reviewing Challenges of Predicting Protein Melting Temperature Change Upon Mutation Through the Full Analysis of a Highly Detailed Dataset with High-Resolution Structures