Abstract RNA modifications are pivotal in the development of newly synthesized structures, showcasing a vast array alterations across various classes. Among these, 5-hydroxymethylcytosine (5HMC) stands out, playing crucial role gene regulation and epigenetic changes, yet its detection through conventional methods proves cumbersome costly. To address this, we propose Deep5HMC, robust learning model leveraging machine algorithms discriminative feature extraction techniques for accurate 5HMC...

Prompt learning has emerged as an efficient alternative for fine-tuning foundational models, such CLIP, various downstream tasks. Conventionally trained using the task-specific objective, i.e., cross-entropy loss, prompts tend to overfit data distributions and find it challenging capture task-agnostic general features from frozen CLIP. This leads loss of model's original generalization capability. To address this issue, our work introduces a self-regularization framework prompting called...

Vision systems to see and reason about the compositional nature of visual scenes are fundamental understanding our world. The complex relations between objects their locations, ambiguities, variations in real-world environment can be better described human language, naturally governed by grammatical rules other modalities such as audio depth. models learned bridge gap coupled with large-scale training data facilitate contextual reasoning, generalization, prompt capabilities at test time....

Although existing semi-supervised learning models achieve remarkable success in with unannotated in-distribution data, they mostly fail to learn on unlabeled data sampled from novel semantic classes due their closed-set assumption. In this work, we target a pragmatic but under-explored Generalized Novel Category Discovery (GNCD) setting. The GNCD setting aims categorize training coming known and by leveraging the information of partially labeled classes. We propose two-stage Contrastive...

With recent advancements in computational biology, high throughput Next-Generation Sequencing (NGS) has become a de facto standard technology for gene expression studies, including DNAs, RNAs, and proteins; however, it generates several millions of sequences single run. Moreover, the raw sequencing datasets are increasing exponentially, doubling size every 18 months, leading to big data issue biology. inflammatory illnesses boosting immune function have recently attracted lot attention, yet...

A novel idea called bipolar complex fuzzy set makes it simple to represent difficult and ambiguous information in practical issues. Confidence levels, set, are three distinct theories that were combined form the basic theory of levels set. (CLBCFS)is used as a method for resolving perplexing suspect circumstances occur daily life. In this article, we define complicated collection confidence levels. To do this, developed number operational laws. Further, utilizing laws, diagnose level...

Post-translational modifications (PTMs) are fundamental to essential biological processes, exerting significant influence over gene expression, protein localization, stability, and genome replication. Sumoylation, a PTM involving the covalent addition of chemical group specific sequence, profoundly impacts functional diversity proteins. Notably, identifying sumoylation sites has garnered attention due their crucial roles in proteomic functions implications various diseases, including...

Binding proteins play a crucial role in biological systems by selectively interacting with specific molecules, such as DNA, RNA, or peptides, to regulate various cellular processes. Their ability recognize and bind target molecules high specificity makes them essential for signal transduction, transport, enzymatic activity. Traditional experimental methods identifying protein-binding peptides are costly time-consuming. Current sequence-based approaches often struggle accuracy, focusing too...

<abstract> <p>Diabetes mellitus is a severe, chronic disease that occurs when blood glucose levels rise above certain limits. Many complications arise if diabetes remains untreated and unidentified. Early prediction of the most high-quality way to forestall manipulate its complications. With rising incidence diabetes, machine learning deep algorithms have been increasingly used predict due their capacity care for massive complicated facts sets. This research aims develop an...

Sumoylation is a post-translation modification (PTM) mechanism that involves many critical biological processes, such as gene expression, localizing and stabilizing proteins, replicating the genome. Moreover, sumoylation sites are associated with different diseases, including Parkinson’s Alzheimer’s. Due to its vital role in process, identifying proteins significant for monitoring protein functions discovering multiple diseases. Therefore, literature, several computational models utilizing...

With recent advancement in computational biology, high throughput next generation sequencing technology has become a de facto standard for genes expression studies including DNAs, RNAs and proteins. As promising technology, it significant impact on medical sciences genomic research. However, generates several millions of short DNA RNA sequences with petabytes size single run. In addition, the raw datasets such as are increasing exponentially leading to big data analytics issue biology. Due...

Enhancers are short DNA regulatory elements which play a vital role in gene expression. Due to their important roles genomics, several computational models have been proposed the literature for identification of enhancers and strengths using traditional machine learning algorithms, however, unable identify strength with reasonable accuracy because high non-linearity sequences. This article proposes two-level intelligent model based on Deep Neural Network (DNN) along multiple feature...

Piwi-interacting Ribonucleic acids (piRNAs) molecule is a well-known subclass of small non-coding RNA molecules that are mainly responsible for maintaining genome integrity, regulating gene expression, and germline stem cell maintenance by suppressing transposon elements. The piRNAs can be used the diagnosis multiple tumor types drug development. Due to vital roles piRNA in computational biology, identification has become an important area research biology. This paper proposes two-layer...