The optimized energy model can be used for multiple predictive applications, including the evaluation of binding free energies for various protein–DNA sequence pairs, prediction of genomic DNA binding ...

Organization Structure Model for Finance. Information about job roles, relationships and communication patterns lies behind the boxes and connections that make up an organizational structure.

Bridging this gap requires a model that can integrate biological sequence input with structural constraints defined by G4 topological formalism. Objectives of the research: To develop a hybrid AI ...

MULAN is a MULtimodal encoder PLM for both sequence and ANgle-based structure processing. MULAN uses the pre-trained base PLM and has the Structure Adapter – a module we introduce to incorporate the ...

Not revised: This Reviewed Preprint includes the authors’ original preprint (without revision), an eLife assessment, public reviews, and a provisional response from the authors. This work presents an ...

The model addresses challenges like enabling structural learning and exposure bias in sequence generation. DPLM-2 effectively co-generates compatible amino acid sequences and 3D structures, ...

The generative pre-trained transformers (GPT) model uses the transformer’s decoder mechanism to predict the next word in a sequence, making it useful for generating relevant text.

It is based on ProtT5-XL-U50, a T5 model trained on encoding protein sequences using span corruption applied on billions of protein sequences. ProstT5 finetunes ProtT5-XL-U50 on translating between ...

1 College of Civil Engineering, Southwest Forestry University, Kunming, China; 2 Hebei Open University, Shijiazhuang, China; 3 School of Civil Engineering, Southwest Jiaotong University, Chengdu, ...

1 Engineering Research Center of Cyberspace, Yunnan University, Kunming, Yunnan, China; 2 School of Software, Yunnan University, Kunming, Yunnan, China; Prediction of the protein secondary structure ...

FormNet is a structure-aware sequence model that bridges the gap between plain sequence models and 2D convolutional models to reduce improper form serialization. The model architecture begins with a ...