11 papers · ranked by Valyu relevance
Dawei Shen, Yao-zhong Zhang, Seiya Imoto
Whole Slide Images (WSIs) are gigapixel, high-resolution digital scans of microscope slides, providing detailed tissue profiles for pathological analysis. Due to their gigapixel size and lack of detailed annotations, Multiple Instance Learning (MIL) becomes the primary technique for WSI analysis. However, current MIL…
Hui Zheng, Hai-Teng Wang, Wei-Bang Jiang, Zhong-Tao Chen + 5 more
While invasive brain-computer interfaces have shown promise for high-performance speech decoding under medical use, the potential of intracranial stereoElectroEn-cephaloGraphy (sEEG), which causes less damage to patients, remains underex-plored. With the rapid progress in representation learning, leveraging abundant…
Mahdi Pourmirzaei, Alex Morehead, Farzaneh Esmaili, Jarett Ren + 2 more
Converting protein tertiary structure into discrete tokens via vector-quantized variational autoencoders (VQ-VAEs) creates a language of 3D geometry and provides a natural interface between sequence and structure models. While pose invariance is commonly enforced, retaining chirality and directional cues without…
Mahdi Pourmirzaei, Alex Morehead, Farzaneh Esmaili, Jarett Ren + 2 more
Converting protein tertiary structure into discrete tokens via vector-quantized variational autoencoders (VQ-VAEs) creates a language of 3D geometry and provides a natural interface between sequence and structure models. While pose invariance is commonly enforced, retaining chirality and directional cues without…
Yusri Dwi Heryanto, Yao-zhong Zhang, Seiya Imoto
Cell-type annotation in single-cell data involves identifying and labeling the cell types based on their gene expression profiles or molecular features. Recently, with advances in single-cell foundation models (FMs), unsupervised annotation and transfer learning with FMs have been explored for cell-type annotation…
Yufeng Liu, Linghui Chen, Haiyan Liu
The power of diffusion probabilistic models (DDPMs) in protein design was recently demonstrated by methods that performs three-dimensional protein backbone denoising. However, these DDPMs tend to generate protein backbones of idealized secondary structures and short loops, lacking diverse, non-idealized local…
Weiyi Xiao, Hegang Chen, Adrien Osakwe, Qihuang Zhang + 1 more
Spatial transcriptomic (ST) technologies enable the measurement of gene expression directly within tissue sections while preserving spatial context. Many ST platforms additionally generate paired histological images alongside spatially resolved transcriptomic profiles. However, most existing computational approaches…
Zhangyang Gao, Cheng Tan, Stan Z. Li
The equivariant nature of 3D coordinates has posed long term challenges in protein structure representation learning, alignment, and generation. Can we create a compact and invariant language that equivariantly represents protein structures? Towards this goal, we propose FoldToken2 to transfer equivariant structures…
Matthew S. Schmitt, Maciej Koch-Janusz, Michel Fruchart, Daniel S. Seara + 2 more
Model reduction is the construction of simple yet predictive descriptions of the dynamics of many-body systems in terms of a few relevant variables. A prerequisite to model reduction is the identification of these relevant variables, a task for which no general method exists. Here, we develop a systematic approach…
Pumiao Yan, Dante G. Muratore, E.J. Chichilnisky, Boris Murmann + 1 more
Scaling neural recording systems to thousands of channels creates extreme bandwidth demands, posing a challenge for resource-constrained, implantable devices. This work introduces an adaptive, multi-stage compression framework for high-bandwidth neural interfaces. The system combines a Wired-OR analog-to-digital…
H. Robert Frost
We present an approach for modeling single cell RNA-sequencing (scRNA-seq) data using quaternions. Quaternions are four dimensional hypercomplex numbers that, along with real numbers, complex numbers and octonions, represent one of the four normed division algebras. Quaternions have been most widely employed to…