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CRISPR-Cas13 is a system that utilizes single stranded RNAs for RNA editing. Prediction of on-target and off-target effects for the CRISPR-Cas13d dependency enables us to design specific single guide RNAs (sgRNAs) that help locate the…

Quantitative Methods · Quantitative Biology 2023-05-12 Jingze Liu , Jiahao Ma

Since the advent of CRISPR-Cas9, a groundbreaking gene-editing technology that enables precise genomic modifications via a short RNA guide sequence, there has been a marked increase in the accessibility and application of this technology…

Quantitative Methods · Quantitative Biology 2024-09-11 Condy Bao , Fuxiao Liu

Multiplex and multi-directional control of metabolic pathways is crucial for metabolic engineering to improve product yield of fuels, chemicals, and pharmaceuticals. To achieve this goal, artificial transcriptional regulators such as…

Biomolecules · Quantitative Biology 2017-04-12 Jiayuan Sheng , Weihua Guo , Christine Ash , Brendan Freitas , Mitchell Paoletti , Xueyang Feng

Gene and RNA editing methods, technologies, and applications are emerging as innovative forms of therapy and medicine, offering more efficient implementation compared to traditional pharmaceutical treatments. Current trends emphasize the…

Genomics · Quantitative Biology 2024-09-17 Mohammed Aledhari , Mohamed Rahouti

CRISPR systems experience off-target effects that interfere with the ability to accurately perform genetic edits. While empirical models predict off-target effects in specific platforms, there is a gap for a wide-ranging mechanistic model…

Biomolecules · Quantitative Biology 2021-09-30 Aset Khakimzhan , David Garenne , Benjamin I. Tickman , Jason Fontana , James Carothers , Vincent Noireaux

In recent years, several machine learning approaches have been proposed to predict gene expression and epigenetic signals from the DNA sequence alone. These models are often used to deduce, and, to some extent, assess putative new…

Genomics · Quantitative Biology 2023-04-26 Laurent Bréhélin

Gene Regulatory Networks (GRNs) are intricate biological systems that control gene expression and regulation in response to environmental and developmental cues. Advances in computational biology, coupled with high throughput sequencing…

Machine Learning · Computer Science 2025-04-18 Akshata Hegde , Tom Nguyen , Jianlin Cheng

CRISPR-Cas systems are an adaptive immunity that protects prokaryotes against foreign genetic elements. Genetic templates acquired during past infection events enable DNA-interacting enzymes to recognize foreign DNA for destruction. Due to…

Genomics · Quantitative Biology 2022-02-16 Hyunjin Shim

The diagnosis of cyber-physical systems aims to detect faulty behaviour, its root cause and a mitigation or even prevention policy. Therefore, diagnosis relies on a representation of the system's functional and faulty behaviour combined…

Machine Learning · Computer Science 2021-10-13 Nicolas Olivain , Philipp Tiefenbacher , Jens Kohl

Cybersecurity is one of the global issues because of the extensive dependence on cyber systems of individuals, industries, and organizations. Among the cyber attacks, phishing is increasing tremendously and affecting the global economy.…

Cryptography and Security · Computer Science 2024-04-30 Md Robiul Islam , Md Mahamodul Islam , Mst. Suraiya Afrin , Anika Antara , Nujhat Tabassum , Al Amin

Genome editing allows scientists to change an organism's DNA. One promising genome editing protocol, already validated in living organisms, is based on clustered regularly interspaced short palindromic repeats (CRISPR)/Cas protein-nucleic…

Biological Physics · Physics 2019-07-25 Angana Ray , Rosa Di Felice

Instruction-following language models often show undesirable biases. These undesirable biases may be accelerated in the real-world usage of language models, where a wide range of instructions is used through zero-shot example prompting. To…

Artificial Intelligence · Computer Science 2024-06-06 Nakyeong Yang , Taegwan Kang , Jungkyu Choi , Honglak Lee , Kyomin Jung

Code changes are an integral part of the software development process. Many code changes are meant to improve the code without changing its functional behavior, e.g., refactorings and performance improvements. Unfortunately, validating…

Software Engineering · Computer Science 2025-02-25 Lars Gröninger , Beatriz Souza , Michael Pradel

Transcriptional profiling on microarrays to obtain gene expressions has been used to facilitate cancer diagnosis. We propose a deep generative machine learning architecture (called DeepCancer) that learn features from unlabeled microarray…

Artificial Intelligence · Computer Science 2016-12-14 Rajendra Rana Bhat , Vivek Viswanath , Xiaolin Li

Recently supervised machine learning has been ascending in providing new predictive approaches for chemical, biological and materials sciences applications. In this Perspective we focus on the interplay of machine learning algorithm with…

This paper presents the framework \textbf{GUARD} (\textbf{G}uided robot control via \textbf{U}ncertainty attribution and prob\textbf{A}bilistic kernel optimization for \textbf{R}isk-aware \textbf{D}ecision making) that combines traditional…

Robotics · Computer Science 2025-09-30 Johannes A. Gaus , Junheon Yoon , Woo-Jeong Baek , Seungwon Choi , Suhan Park , Jaeheung Park

Propelled partly by the Materials Genome Initiative, and partly by the algorithmic developments and the resounding successes of data-driven efforts in other domains, informatics strategies are beginning to take shape within materials…

Materials Science · Physics 2017-07-25 Rampi Ramprasad , Rohit Batra , Ghanshyam Pilania , Arun Mannodi-Kanakkithodi , Chiho Kim

Cybercrime is a growing threat to organizations and individuals worldwide, with criminals using sophisticated techniques to breach security systems and steal sensitive data. This paper aims to comprehensively survey the latest advancements…

Machine Learning · Computer Science 2023-10-12 Lavanya Elluri , Varun Mandalapu , Piyush Vyas , Nirmalya Roy

Use of computational methods to predict gene regulatory networks (GRNs) from gene expression data is a challenging task. Many studies have been conducted using unsupervised methods to fulfill the task; however, such methods usually yield…

Machine Learning · Computer Science 2016-08-15 Nihir Patel , Jason T. L. Wang

Predicting guide RNA (gRNA) activity is critical for effective CRISPR-Cas12 genome editing but remains challenging due to limited data, variation across protospacer adjacent motifs (PAMs-short sequence requirements for Cas binding), and…

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