Providing a scientific forum for practical applications and theoretical advances of Artificial Intelligence (AI) in the life sciences and related disciplines including (but not restricted to):New AI methods for life science researchAdaptation of existing AI concepts for life science applicationsApplication of AI approaches in: Molecular and systems biologyPopulation and disease geneticsBio- and cheminformaticsMedicinal chemistry, chemical biology, and drug discoveryMedical researchPublications are required to contain substantial AI and life science components. Clinical studies reporting routine diagnostic efforts hall outside the scope of AILSCI.Background: Artificial Intelligence originates from computer science and covers a wide range of approaches intended to enhance the ability of machines to make data-driven decisions and accurate predictions of events. In many scientific fields, AI is being increasingly considered and integrated, especially in the context of Big Data. Given their complexity and highly interdisciplinary nature, the life sciences provide ample opportunities for AI to impact R&D efforts in a variety of ways.Key words: Artificial Intelligence; Life Sciences; Drug Discovery; Bio- and Cheminformatics, Machine Learning; Machine Intelligence; Deep Learning; Data Mining; Big Data.
Following the merger of Computer Languages, Systems and Structures with the Journal of Visual Languages and Computing in 2018, we are excited to present the Journal of Computer Languages, a single publication which covers all areas of computer languages.The Journal of Computer Languages (COLA) welcomes papers on all aspects of the design, implementation, and use of computer languages (specification, modelling, programming; textual or visual) and human-centric computing, from theory to practice. Most papers describe original technical research, but the journal also welcome empirical studies and survey articles.Current research areas for the Journal of Computer Languages include:Block-based languagesCognitive, perceptive and motoric systems and modelsCompilers and interpretersComputational thinkingDesign and development of concurrent, distributed, parallel, quantum and sequential languagesDomain-specific languagesEnd-user developmentGenerative approaches, meta-programming, meta-modellingHuman aspects and psychology of designing languagesInformation visualizationInteraction models and languagesLocation-based data and processesLanguage design and implementationLanguage-based securityLanguage evolution, integration, composition, and coordinationLanguage product linesLanguage workbenches, meta-languages and development frameworksLanguages, models, and frameworks for visual analyticsLanguages for large-scale scientific computingLanguages for software specification and verificationLibraries, run-time environments and language ecosystemsModelling and programming languagesModularity and extensibility of language specifications and programmingParallel/distributed/neural computing and representations for visual information processingPattern languagesPictorial systems and languagesProgram analysis and optimizationProgram comprehensionProgram visualization and animationProgramming environments and toolsProgramming paradigms (agent-oriented, aspect-oriented, intermittent, etc.)Scientific visualizationScripting languagesSemantics of computer languagesSemantics-based verificationSoftware language engineeringSoftware visualizationType systemsUser interface design languagesVisual languages and programming
The Open Access Natural Language Processing Journal aims to advance modern understanding and practice of trustworthy, interpretable, explainable human-centered and hybrid Artificial Intelligence as it relates to all aspects of human language. The NLP journal affords a world-wide platform for academics and practitioners to present their latest theoretical, practical, and methodological research concerning the development and application of trustworthy AI to analyze, process, or model human language across various multimodal contexts, domains, and intelligent systems, including hybrid AI , Human AI interaction and Social systems. The NLP journal welcomes original research papers, review papers, position papers, tutorial and best practice papers. Special Issues proposals on specific current topics are welcomed. To foster trust, transparency, and reproducibility in AI research the NLP journal promotes open and FAIR data and software sharing practices. Furthermore the NLP journal specifically invites researchers to submit scientific replication studies for review and publication.