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Related papers: ProtiGeno: a prokaryotic short gene finder using p…

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The interaction between proteins and DNA is a key driving force in a significant number of biological processes such as transcriptional regulation, repair, recombination, splicing, and DNA modification. The identification of DNA-binding…

Quantitative Methods · Quantitative Biology 2017-05-10 Hamid Reza Hassanzadeh , Pushkar Kolhe , Charles L. Isbell , May D. Wang

Shaped by natural selection and other evolutionary forces, an organism's evolutionary history is reflected through its genome sequence, content of functional elements and organization. Consequently, organisms connected through phylogeny,…

Genomics · Quantitative Biology 2023-06-16 Serena Lam , Giorgio Gonnella

Recent advances in generative modeling show that pretrained representations can improve generation as conditioning features or alignment targets. Motivated by this, we study protein representations for predicting structures beyond…

Biomolecules · Quantitative Biology 2026-05-27 Taewon Kim , Hyosoon Jang , Hyunjin Seo , Seonghwan Seo , Hyeongwoo Kim , Wonho Zhung , Mingyeong Shin , Wooyoun Kim , Sungsoo Ahn

Structure-based drug design is drawing growing attentions in computer-aided drug discovery. Compared with the virtual screening approach where a pre-defined library of compounds are computationally screened, de novo drug design based on the…

Biomolecules · Quantitative Biology 2022-09-14 Kehan Wu , Yingce Xia , Yang Fan , Pan Deng , Haiguang Liu , Lijun Wu , Shufang Xie , Tong Wang , Tao Qin , Tie-Yan Liu

Each human genome is a 3 billion base pair set of encoding instructions. Decoding the genome using deep learning fundamentally differs from most tasks, as we do not know the full structure of the data and therefore cannot design…

Machine Learning · Computer Science 2016-05-24 Laura Deming , Sasha Targ , Nate Sauder , Diogo Almeida , Chun Jimmie Ye

Designing protein sequences that fold into a target 3-D structure, termed as the inverse folding problem, is central to protein engineering. However, it remains challenging due to the vast sequence space and the importance of local…

Quantitative Methods · Quantitative Biology 2026-03-17 Sazan Mahbub , Souvik Kundu , Eric P. Xing

Current metagenomic analysis algorithms require significant computing resources, can report excessive false positives (type I errors), may miss organisms (type II errors / false negatives), or scale poorly on large datasets. This paper…

Databases · Computer Science 2015-01-23 Ashley Mae Conard , Stephanie Dodson , Jeremy Kepner , Darrell Ricke

Protein structures are important for understanding their functions and interactions. Currently, many protein structure prediction methods are enriching the structure database. Discriminating the origin of structures is crucial for…

Biomolecules · Quantitative Biology 2024-10-24 Wenrui Gou , Wenhui Ge , Yang Tan , Mingchen Li , Guisheng Fan , Huiqun Yu

We present a novel method for finding low dimensional views of high dimensional data: Targeted Projection Pursuit. The method proceeds by finding projections of the data that best approximate a target view. Two versions of the method are…

Quantitative Methods · Quantitative Biology 2007-05-23 J. Faith , R. Mintram , M. Angelova

BACKGROUND: Breast cancer has emerged as one of the most prevalent cancers among women leading to a high mortality rate. Due to the heterogeneous nature of breast cancer, there is a need to identify differentially expressed genes associated…

Machine Learning · Computer Science 2021-11-30 Sheetal Rajpal , Ankit Rajpal , Manoj Agarwal , Naveen Kumar

In recent years, the sequencing, assembling and annotation of prokaryotic genomes has become increasingly easy and cheap. Thus it becomes increasingly feasible and interesting to perform comparative genomics analyses of new genomes to those…

Genomics · Quantitative Biology 2023-05-08 Giorgio Gonnella

New powerful tools for tackling life science problems have been created by recent advances in machine learning. The purpose of the paper is to discuss the potential advantages of gene recommendation performed by artificial intelligence…

Quantitative Methods · Quantitative Biology 2023-03-23 Daniele Brambilla , Davide Maria Giacomini , Luca Muscarnera , Andrea Mazzoleni

Determining the full complement of protein-coding genes is a key goal of genome annotation. The most powerful approach for confirming protein coding potential is the detection of cellular protein expression through peptide mass spectrometry…

Current protein language models (PLMs) learn protein representations mainly based on their sequences, thereby well capturing co-evolutionary information, but they are unable to explicitly acquire protein functions, which is the end goal of…

Biomolecules · Quantitative Biology 2023-07-06 Minghao Xu , Xinyu Yuan , Santiago Miret , Jian Tang

Phylogenetic trees elucidate evolutionary relationships among species, but phylogenetic inference remains challenging due to the complexity of combining continuous (branch lengths) and discrete parameters (tree topology). Traditional Markov…

Populations and Evolution · Quantitative Biology 2024-12-30 ChenRui Duan , Zelin Zang , Siyuan Li , Yongjie Xu , Stan Z. Li

Directed evolution is a versatile technique in protein engineering that mimics the process of natural selection by iteratively alternating between mutagenesis and screening in order to search for sequences that optimize a given property of…

Biomolecules · Quantitative Biology 2024-05-02 Lixue Cheng , Ziyi Yang , Changyu Hsieh , Benben Liao , Shengyu Zhang

De novo molecule generation often results in chemically unfeasible molecules. A natural idea to mitigate this problem is to bias the search process towards more easily synthesizable molecules using a proxy for synthetic accessibility.…

Motivation: The gene content regulates the biology of an organism. It varies between species and between individuals of the same species. Although tools have been developed to identify gene content changes in bacterial genomes, none is…

Genomics · Quantitative Biology 2024-05-30 Heng Li , Maximillian Marin , Maha Reda Farhat

Machine Learning methods have of late made significant efforts to solving multidisciplinary problems in the field of cancer classification using microarray gene expression data. Feature subset selection methods can play an important role in…

Computational Engineering, Finance, and Science · Computer Science 2013-03-04 G. Prat , Ll. Belanche

Deep neural network-based architectures give promising results in various domains including pattern recognition. Finding the optimal combination of the hyper-parameters of such a large-sized architecture is tedious and requires a large…

Computer Vision and Pattern Recognition · Computer Science 2020-03-17 Animesh Singh , Sandip Saha , Ritesh Sarkhel , Mahantapas Kundu , Mita Nasipuri , Nibaran Das
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