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1. Grounded Sequence to Sequence Transduction

   https://doi.org/10.1109/JSTSP.2020.2998415  

   Lucia Specia, Loıc Barrault ( July 2020 , IEEE journal of selected topics in signal processing)

   null (Ed.)

   Speech recognition and machine translation have made major progress over the past decades, providing practical systems to map one language sequence to another. Although multiple modalities such as sound and video are becoming increasingly available, the state-of-the-art systems are inherently unimodal, in the sense that they take a single modality --- either speech or text --- as input. Evidence from human learning suggests that additional modalities can provide disambiguating signals crucial for many language tasks. Here, we describe the dataset, a large, open-domain collection of videos with transcriptions and their translations. We then show how this single dataset can be used to develop systems for a variety of language tasks and present a number of models meant as starting points. Across tasks, we find that building multi-modal architectures that perform better than their unimodal counterpart remains a challenge. This leaves plenty of room for the exploration of more advanced solutions that fully exploit the multi-modal nature of the dataset, and the general direction of multimodal learning with other datasets as well. 

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2. The role of filamentation in activation and DNA sequence specificity of the sequence-specific endonuclease SgrAI

   https://doi.org/10.1042/BST20220547  

   Lyumkis, Dmitry ; Horton, Nancy C. ( November 2022 , Biochemical Society Transactions)

   Filament formation by metabolic, biosynthetic, and other enzymes has recently come into focus as a mechanism to fine-tune enzyme activity in the cell. Filamentation is key to the function of SgrAI, a sequence-specific DNA endonuclease that has served as a model system to provide some of the deepest insights into the biophysical characteristics of filamentation and its functional consequences. Structure-function analyses reveal that, in the filamentous state, SgrAI stabilizes an activated enzyme conformation that leads to accelerated DNA cleavage activity and expanded DNA sequence specificity. The latter is thought to be mediated by sequence-specific DNA structure, protein–DNA interactions, and a disorder-to-order transition in the protein, which collectively affect the relative stabilities of the inactive, non-filamentous conformation and the active, filamentous conformation of SgrAI bound to DNA. Full global kinetic modeling of the DNA cleavage pathway reveals a slow, rate-limiting, second-order association rate constant for filament assembly, and simulations of in vivo activity predict that filamentation is superior to non-filamenting mechanisms in ensuring rapid activation and sequestration of SgrAI's DNA cleavage activity on phage DNA and away from the host chromosome. In vivo studies demonstrate the critical requirement for accelerated DNA cleavage by SgrAI in its biological role to safeguard the bacterial host. Collectively, these data have advanced our understanding of how filamentation can regulate enzyme structure and function, while the experimental strategies used for SgrAI can be applied to other enzymatic systems to identify novel functional roles for filamentation. 

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3. Sequence-to-Sequence Networks Learn the Meaning of Reflexive Anaphora

   Frank, Robert ; Petty, Jackson ( December 2020 , Proceedings of the 3rd Workshop on Computational Models of Reference, Anaphora and Coreference (CRAC 2020))

   null (Ed.)
4. The optimal sequence of prices and auctions

   https://doi.org/10.1016/j.euroecorev.2021.103681  

   Zhang, Hanzhe ( April 2021 , European Economic Review)

   null (Ed.)
5. Sequence-based classification and identification of Fungi

   https://doi.org/10.3852/16-130  

   Hibbett, D ; Abarenkov, K. ; Kõljalg, U. ; Öpik, M. ; Chai, B. ; Cole, J. ; Wang, Q. ; Crous, P. ; Robert, V. ; Helgason, T. ; et al ( January 2017 , Mycologia)

   Fungal taxonomy and ecology have been revolutionized by the application of molecular methods and both have increasing connections to genomics and functional biology. However, data streams from traditional specimen- and culture-based systematics are not yet fully integrated with those from metagenomic and metatranscriptomic studies, which limits understanding of the taxonomic diversity and metabolic properties of fungal communities. This article reviews current resources, needs, and opportunities for sequence-based classification and identification (SBCI) in fungi as well as related efforts in prokaryotes. To realize the full potential of fungal SBCI it will be necessary to make advances in multiple areas. Improvements in sequencing methods, including long-read and single-cell technologies, will empower fungal molecular ecologists to look beyond ITS and current shotgun metagenomics approaches. Data quality and accessibility will be enhanced by attention to data and metadata standards and rigorous enforcement of policies for deposition of data and workflows. Taxonomic communities will need to develop best practices for molecular characterization in their focal clades, while also contributing to globally useful datasets including ITS. Changes to nomenclatural rules are needed to enable validPUBLICation of sequence-based taxon descriptions. Finally, cultural shifts are necessary to promote adoption of SBCI and to accord professional credit to individuals who contribute to community resources. 

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