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In this paper, we develop the iAVPs-ResBi model using k-spaced amino acid pairs (KSAAP), encoding based on grouped weight (EBGW), enhanced grouped amino acid composition (EGAAC) based on the N5C5 sequence, composition, transition and distribution (CTD) based on physicochemical properties for multi-feature extraction. Then we adopt bidirectional long short-term memory (BiLSTM) to fuse features for obtaining the most differentiated information from multiple original feature sets. Finally, the deep model is built by combining improved residual network and bidirectional gated recurrent unit (BiGRU) to perform classification. The results obtained are better than those of the existing methods, and the accuracies are 95.07, 98.07, 94.29 and 97.50% on the four datasets, which show that iAVPs-ResBi can be used as an effective tool for the identification of antiviral peptides. The datasets and codes are freely available at https:\/\/github.com\/yunyunliang88\/iAVPs-ResBi.&lt;\/p&gt;\n\n\t      &lt;\/abstract&gt;<\/jats:p>","DOI":"10.3934\/mbe.2023954","type":"journal-article","created":{"date-parts":[[2023,12,6]],"date-time":"2023-12-06T03:17:31Z","timestamp":1701832651000},"page":"21563-21587","source":"Crossref","is-referenced-by-count":3,"title":["iAVPs-ResBi: Identifying antiviral peptides by using deep residual network and bidirectional gated recurrent unit"],"prefix":"10.3934","volume":"20","author":[{"given":"Xinyan","family":"Ma","sequence":"first","affiliation":[{"name":"School of Science, Xi'an Polytechnic University, Xi'an 710048, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunyun","family":"Liang","sequence":"additional","affiliation":[{"name":"School of Science, Xi'an Polytechnic University, Xi'an 710048, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shengli","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, Xidian University, Xi'an 710071, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2321","reference":[{"key":"key-10.3934\/mbe.2023954-1","doi-asserted-by":"publisher","unstructured":"E. 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