24 papers · ranked by Valyu relevance
Peter Heringer, Daniel Doerr
Pangenome graphs offer a compact and comprehensive representation of genomic diversity, improving tasks such as variant calling, genotyping, and other downstream analyses. Although the underlying graph structures scale sublinearly with the number of haplotypes, the widely used GFA file format suffers from rapidly…
Qi Liu, Yu Yang, Chun Chen, Jiajun Bu + 2 more
Background With the rapid emergence of RNA databases and newly identified non-coding RNAs, an efficient compression algorithm for RNA sequence and structural information is needed for the storage and analysis of such data. Although several algorithms for compressing DNA sequences have been proposed, none of them are…
Jie Zhang, En‐hui Yang, John C. Kieffer
We consider the problem of lossless compression of binary trees, with the aim of reducing the number of code bits needed to store or transmit such trees. A lossless grammar-based code is presented which encodes each binary tree into a binary codeword in two steps. In the first step, the tree is transformed into a…
Sean Deyo, Veit Elser
We introduce the logical grammar emdebbing (LGE), a model inspired by pregroup grammars and categorial grammars to enable unsupervised inference of lexical categories and syntactic rules from a corpus of text. LGE produces comprehensible output summarizing its inferences, has a completely transparent process for…
Jonathan Dunn
This paper uses the Minimum Description Length paradigm to model the complexity of CxGs (operationalized as the encoding size of a grammar) alongside their descriptive adequacy (operationalized as the encoding size of a corpus given a grammar). These two quantities are combined to measure the quality of potential CxGs…
Rahul Varki, Travis Gagie, Christina Boucher
Among grammar-based compression techniques, RePair is a notable offline encoding scheme known for its simplicity and powerful combinatorial properties, producing compact grammars by repeatedly replacing the most frequent adjacent pairs of symbols, known as bigrams. However, RePair’s memory usage scales poorly with…
Isamu Furuya
The goal of grammar compression is to construct a small sized context free grammar which uniquely generates the input text data. Among grammar compression methods, RePair is known for its good practical compression performance. MR-RePair was recently proposed as an improvement to RePair for constructing small-sized…
Sanjay Nag, Nabanita Basu, Payal Bose, Samir Kumar Bandyopadhyay + 1 more
'Yunfeng Wu'] Disease prediction using computer-based methods is now an established area of research. The importance of technological intervention is necessary for the better management of disease, as well as to optimize use of limited resources. Various AI-based methods for disease prediction have been documented in…
Lucas Y. Tian, Daniel J. Hanuska, Kedar Garzón Gupta, Yue Liu + 3 more
Humans and other animals can solve new problems, even on the first attempt. This capacity to generate novel problem-solving behavior has been hypothesized to depend on brain mechanisms for recombining units of knowledge using systems of procedural rules, or grammars. Yet, whether and how the brain represents and…
Rohit J Kate
Background Clinical reports are written using a subset of natural language while employing many domain-specific terms; such a language is also known as a sublanguage for a scientific or a technical domain. Different genres of clinical reports use different sublaguages, and in addition, different medical facilities use…
Richard Apodaca
Despite its widespread use, Simplified Molecular Input Line Entry System (SMILES) remains underspecified. The lack of a detailed specification encourages improvisation by software developers, complicates data standardization efforts, and undermines extension development. Balsa, a reformulation of SMILES, addresses…
Subhankar Roy, Dilip Kumar Maity, Anirban Mukhopadhyay
Deoxyribonucleic acid (DNA) or ribonucleic acid (RNA) sequence compressors for novel species frequently face challenges when processing wide-scale raw, FASTA, or multi-FASTA structured data. For years, molecular sequence databases have favored the widely used general-purpose Gzip and Zstd compressors. The absence of…
Lin Sun, Sanjay G Manohar
Syntax is a central organizing component of human language but few models explain how it may be implemented in neurons. We combined two rapid synaptic rules to demonstrate how neurons can implement a simple grammar without accounting for the hierarchical property of syntax. Words bind to syntactic roles (e.g. “dog” as…
Justin Kim, Rahul Varki, Marco Oliva, Christina Boucher
The RePair compression algorithm produces a context-free grammar by iteratively substituting the most frequently occurring pair of consecutive symbols with a new symbol until all consecutive pairs of symbols appear only once in the compressed text. It is widely used in the settings of bioinformatics, machine learning…
Luís F Seoane, Ricard Solé
What are relevant levels of description when investigating human language? How are these levels connected to each other? Does one description yield smoothly into the next one such that different models lie naturally along a hierarchy containing each other? Or, instead, are there sharp transitions between one…
Michał Gańczorz
In grammar compression we represent a string as a context free grammar. This model is popular both in theoretical and practical applications due to its simplicity, good compression rate and suitability for processing of the compressed representations. In practice, achieving compression requires encoding such grammar as…
Johannes T. Margraf, Zachary W. Ulissi, Yousung Jung, Karsten Reuter
The discovery of new catalytically active materi- als is one of the holy grails of computational chemistry as it has the potential to accelerate the adoption of renewable energy sources and reduce the energy consumption of chemical industry. Indeed, heterogeneous catalysts are essential for the production of synthetic…
Zijian Liang, Kai Niu, Jin Xu, Ping Zhang + 1 more
Recent semantic communication methods explore effective ways to expand the communication paradigm and improve the performance of communication systems. Nonetheless, a common problem with these methods is that the essence of semantics is not explicitly pointed out and directly utilized. A new epistemology suggests that…
Kaixuan Zhang, Qinglong Wang, C. Lee Giles
Recently, there has been a resurgence of formal language theory in deep learning research. However, most research focused on the more practical problems of attempting to represent symbolic knowledge by machine learning. In contrast, there has been limited research on exploring the fundamental connection between them.…
Authors not listed
RNA molecules fold into complex three-dimensional structures that determine their function. A wide range of mathematical frameworks, such as chord diagrams, fatgraphs, and context-free grammars, have been used to represent these structures; however, these models have largely been developed from mathematical motivations…
Morgan Thomas, Mazen Ahmad, Gary Tresadern, Gianni de Fabritiis
SMILES-based generative models are amongst the most robust and successful recent methods used to augment drug design. They are typically used for complete de novo generation, however, scaffold decoration and fragment linking applications are sometimes desirable which requires a different architecture, a different…
Lanzhi Cheng, Peiyun Ben, Yuchen Qiao
As one of the most widely used languages in the world, English plays a vital role in the communication between China and the world. However, grammar learning in English is a difficult and long process for English learners. Especially in English writing, English learners will inevitably make various grammatical writing…
Authors not listed
Deep generative models are transforming early-stage drug discovery, yet most current approaches are not well suited for realistic, small-data settings and often rely on simplified molecular representations such as linear strings, overlooking the inherent graph-based structure of molecules. To address this, we first…
Sanjar Adilov
Generative neural networks have shown promising results in de novo drug design. Recent studies suggest that one of the efficient ways to produce novel molecules matching target properties is to model SMILES sequences using deep learning in a way similar to language modeling in natural language processing. In this…