Steering Protein Family Design through Profile Bayesian Flow | Paper Citation Record

Observation f3b78f61-d7c4-4be0-8695-78422615e820 · outbound

This paper cites Accurate structure prediction of biomolecular interactions with alphafold 3.

Steering Protein Family Design through Profile Bayesian Flow Accurate structure prediction of biomolecular interactions with alphafold 3

Reference 1

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Observation eb8cbe8f-ee14-4367-aa89-d925155cd126 · outbound

This paper cites Rosettaantibodydesign (rabd): A general framework for computational antibody design.

Steering Protein Family Design through Profile Bayesian Flow Rosettaantibodydesign (rabd): A general framework for computational antibody design

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.920167Z

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Observation a88b2c2b-ba96-494e-9701-131aa0e2d3e4 · outbound

This paper cites Protein generation with evolutionary diffusion: sequence is all you need.

Steering Protein Family Design through Profile Bayesian Flow Protein generation with evolutionary diffusion: sequence is all you need

Reference 3

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Observation 5b32534a-562b-4c04-a013-be441965c2d1 · outbound

This paper cites Exploring the predictive capabilities of alphafold using adversarial protein sequences.

Steering Protein Family Design through Profile Bayesian Flow Exploring the predictive capabilities of alphafold using adversarial protein sequences

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.887522Z

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Observation 5aa3e959-2bd3-441d-bb8e-cd3c8e28cbd7 · outbound

This paper cites Design by directed evolution.

Steering Protein Family Design through Profile Bayesian Flow Design by directed evolution

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.871900Z

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Observation dbd847d1-bd42-42cb-ac9e-31e531f7e3f5 · outbound

This paper cites Synthetic biology.

Steering Protein Family Design through Profile Bayesian Flow Synthetic biology

Reference 6

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Observation 90bc8582-3007-45db-9e8f-3cc0cdba1c62 · outbound

This paper cites In the light of directed evolution: pathways of adaptive protein evolution.

Steering Protein Family Design through Profile Bayesian Flow In the light of directed evolution: pathways of adaptive protein evolution

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.839146Z

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Observation 1c78b192-0ab9-4a61-8fa1-28633729f9c4 · outbound

This paper cites MSAGPT: Neural Prompting Protein Structure Prediction via MSA Generative Pre-Training.

Steering Protein Family Design through Profile Bayesian Flow MSAGPT: Neural Prompting Protein Structure Prediction via MSA Generative Pre-Training

Reference 8

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Observation fc74f445-0368-43f5-b21f-e9ba7c2d1e4b · outbound

This paper cites Uniprot: a hub for protein information.

Steering Protein Family Design through Profile Bayesian Flow Uniprot: a hub for protein information

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.823715Z

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Observation c044e3f9-eaea-47d3-bdf3-be86963ffc68 · outbound

This paper cites De novo protein design: fully automated sequence selection.

Steering Protein Family Design through Profile Bayesian Flow De novo protein design: fully automated sequence selection

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.807673Z

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Observation b2119f4a-427c-4b3d-8af5-6d888da9848e · outbound

This paper cites Flip: Benchmark tasks in fitness landscape inference for proteins.

Steering Protein Family Design through Profile Bayesian Flow Flip: Benchmark tasks in fitness landscape inference for proteins

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.791622Z

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Observation 7638a744-1254-4a59-a0a3-ff804cfe0d07 · outbound

This paper cites Multiple sequence alignment.

Steering Protein Family Design through Profile Bayesian Flow Multiple sequence alignment

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.773642Z

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Observation 4973b8ef-1525-4c19-8e92-b6cb91e989a0 · outbound

This paper cites Bayesian Flow Networks.

Steering Protein Family Design through Profile Bayesian Flow Bayesian Flow Networks

Reference 13

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Observation 1636a4c2-6333-441b-b85f-76c3cfc67d74 · outbound

This paper cites Protein sequence analysis.

Steering Protein Family Design through Profile Bayesian Flow Protein sequence analysis

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.757522Z

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Observation 54a865b1-745d-468b-becb-b2e334fe0de7 · outbound

This paper cites Simulating 500 million years of evolution with a language model.

Steering Protein Family Design through Profile Bayesian Flow Simulating 500 million years of evolution with a language model

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.743535Z

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Observation 11faf91a-3882-4792-9afe-e02d6865be47 · outbound

This paper cites Amino acid substitution matrices from protein blocks.

Steering Protein Family Design through Profile Bayesian Flow Amino acid substitution matrices from protein blocks

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.729417Z

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Observation 64258461-b42d-4079-8b58-0706774423d0 · outbound

This paper cites Precision medicine, ai, and the future of personalized health care.

Steering Protein Family Design through Profile Bayesian Flow Precision medicine, ai, and the future of personalized health care

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.714694Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9258a27d-a1cd-4cb7-b0e5-9e75cf8d5dce · outbound

This paper cites Highly accurate protein structure prediction with alphafold.

Steering Protein Family Design through Profile Bayesian Flow Highly accurate protein structure prediction with alphafold

Reference 18

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Observation 1a470d3d-db65-422e-821b-8fd1b648f4b8 · outbound

This paper cites A comprehensive evolutionary classification of proteins encoded in complete eukaryotic genomes.

Steering Protein Family Design through Profile Bayesian Flow A comprehensive evolutionary classification of proteins encoded in complete eukaryotic genomes

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.687933Z

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Observation 734a9d1f-2680-42bb-8a2d-ec7a46143dc1 · outbound

This paper cites Precision medicine.

Steering Protein Family Design through Profile Bayesian Flow Precision medicine

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.672210Z

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Observation 9af4a18f-2b87-4ab8-883e-63e3e6b57ef9 · outbound

This paper cites Language models of protein sequences at the scale of evolution enable accurate structure prediction.

Steering Protein Family Design through Profile Bayesian Flow Language models of protein sequences at the scale of evolution enable accurate structure prediction

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-08T12:02:08.973188Z

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Observation 20fd1d75-a762-422a-9797-40125962f8a9 · outbound

This paper cites Evolutionary-scale prediction of atomic-level protein structure with a language model.

Steering Protein Family Design through Profile Bayesian Flow Evolutionary-scale prediction of atomic-level protein structure with a language model

Reference 22

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Observation 7699f978-d53c-40a3-91d3-07afa614395e · outbound

This paper cites Msa-cuda: multiple sequence alignment on graphics processing units with cuda.

Steering Protein Family Design through Profile Bayesian Flow Msa-cuda: multiple sequence alignment on graphics processing units with cuda

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.635502Z

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Observation d2e6f762-36f2-421c-9f1a-94de48152612 · outbound

This paper cites Decoupled Weight Decay Regularization.

Steering Protein Family Design through Profile Bayesian Flow Decoupled Weight Decay Regularization

Reference 24

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Observation 1d57af3b-340d-4833-8fac-1e0100f64c78 · outbound

This paper cites Antigen-specific antibody design and optimization with diffusion-based generative models for protein structures.

Steering Protein Family Design through Profile Bayesian Flow Antigen-specific antibody design and optimization with diffusion-based generative models for protein structures

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.620071Z

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Observation 5f19b651-a517-4923-aee1-9fd887d59564 · outbound

This paper cites A unified analysis of evolutionary and population constraint in protein domains highlights structural features and pathogenic sites.

Steering Protein Family Design through Profile Bayesian Flow A unified analysis of evolutionary and population constraint in protein domains highlights structural features and pathogenic sites

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.603783Z

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Observation 10a03715-6621-488e-8a10-c2f8a8d39aa8 · outbound

This paper cites ProGen: Language Modeling for Protein Generation.

Steering Protein Family Design through Profile Bayesian Flow ProGen: Language Modeling for Protein Generation

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-08T12:02:09.003805Z

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Observation 3d0a225a-69e0-4f97-bd67-e19d6c964188 · outbound

This paper cites Large language models generate functional protein sequences across diverse families.

Steering Protein Family Design through Profile Bayesian Flow Large language models generate functional protein sequences across diverse families

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.587473Z

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Observation 32ac97be-e5af-4538-af18-85b6c20e7e06 · outbound

This paper cites Language models enable zero-shot prediction of the effects of mutations on protein function.

Steering Protein Family Design through Profile Bayesian Flow Language models enable zero-shot prediction of the effects of mutations on protein function

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-08T12:02:09.015269Z

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Observation 68cd50b7-4a65-407f-8fad-bebc837f21b6 · outbound

This paper cites Improved structure-related prediction for insufficient homologous proteins using msa enhancement and pre-trained language model.

Steering Protein Family Design through Profile Bayesian Flow Improved structure-related prediction for insufficient homologous proteins using msa enhancement and pre-trained language model

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.571441Z

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Observation 1e6c01a8-7fe9-432a-a204-5951bdec35ab · outbound

This paper cites Uniclust databases of clustered and deeply annotated protein sequences and alignments.

Steering Protein Family Design through Profile Bayesian Flow Uniclust databases of clustered and deeply annotated protein sequences and alignments

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.555607Z

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Observation d377f070-efe8-484b-a2be-3c7cff24d9c9 · outbound

This paper cites A heuristic approach to high-speed multiple sequence alignment for phylogenetic tree construction.

Steering Protein Family Design through Profile Bayesian Flow A heuristic approach to high-speed multiple sequence alignment for phylogenetic tree construction

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.540210Z

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Observation e94dbd40-366d-4175-8da9-7178d8a2ca2e · outbound

This paper cites Progen2: exploring the boundaries of protein language models.

Steering Protein Family Design through Profile Bayesian Flow Progen2: exploring the boundaries of protein language models

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.524204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 771b4d2a-30d5-47f1-bff1-f534e11ffb1b · outbound

This paper cites Ablang: an antibody language model for completing antibody sequences.

Steering Protein Family Design through Profile Bayesian Flow Ablang: an antibody language model for completing antibody sequences

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.508321Z

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Observation 34e5b132-b649-4d94-83af-9517f2fd2ba0 · outbound

This paper cites Methods for the directed evolution of proteins.

Steering Protein Family Design through Profile Bayesian Flow Methods for the directed evolution of proteins

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.493208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a633a5dd-919f-4ed7-a9d4-ecc6c822ff84 · outbound

This paper cites Msa transformer.

Steering Protein Family Design through Profile Bayesian Flow Msa transformer

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.478490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 277ce5a9-e048-4fbd-9cc4-f7c9ae5473d1 · outbound

This paper cites Hhblits: lightning-fast iterative protein sequence searching by hmm-hmm alignment.

Steering Protein Family Design through Profile Bayesian Flow Hhblits: lightning-fast iterative protein sequence searching by hmm-hmm alignment

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.464341Z

Source-reported events for the cited work

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Observation 3ecc072a-d9cc-4bec-97b7-53bcc1254ec6 · outbound

This paper cites Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences.

Steering Protein Family Design through Profile Bayesian Flow Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.449474Z

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Observation 8fd2cc5c-b89e-4ed9-ac3f-7c6d05800d7c · outbound

This paper cites Continuous automated model evaluation (cameo)—perspectives on the future of fully automated evaluation of structure prediction methods.

Steering Protein Family Design through Profile Bayesian Flow Continuous automated model evaluation (cameo)—perspectives on the future of fully automated evaluation of structure prediction methods

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.433251Z

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Observation f483ecf6-29c7-492e-a2dc-72f31d561e31 · outbound

This paper cites Deciphering antibody affinity maturation with language models and weakly supervised learning.

Steering Protein Family Design through Profile Bayesian Flow Deciphering antibody affinity maturation with language models and weakly supervised learning

Reference 40

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Source-reported events for the cited work

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Observation 1235e472-2625-4d55-8518-30a4e1aed1e3 · outbound

This paper cites Ccmpred—fast and precise prediction of protein residue--residue contacts from correlated mutations.

Steering Protein Family Design through Profile Bayesian Flow Ccmpred—fast and precise prediction of protein residue--residue contacts from correlated mutations

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.416392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8f8d7fd3-178e-4c52-879d-cfbaea8a409e · outbound

This paper cites Protmamba: a homology-aware but alignment-free protein state space model.

Steering Protein Family Design through Profile Bayesian Flow Protmamba: a homology-aware but alignment-free protein state space model

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.398758Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ae7769f5-51b1-4e5d-8681-6e3fc6557202 · outbound

This paper cites Generative enzyme design guided by functionally important sites and small-molecule substrates.

Steering Protein Family Design through Profile Bayesian Flow Generative enzyme design guided by functionally important sites and small-molecule substrates

Reference 43

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Observation b4ca6bb2-8d51-40d8-8f94-c320b87628ff · outbound

This paper cites Mmseqs2 enables sensitive protein sequence searching for the analysis of massive data sets.

Steering Protein Family Design through Profile Bayesian Flow Mmseqs2 enables sensitive protein sequence searching for the analysis of massive data sets

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.382961Z

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Observation 625dcab8-ac23-49b9-852c-4c3f4173cf14 · outbound

This paper cites Saprot: Protein language modeling with structure-aware vocabulary.

Steering Protein Family Design through Profile Bayesian Flow Saprot: Protein language modeling with structure-aware vocabulary

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.367011Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 399e23cc-a850-437e-9587-429d45b3b458 · outbound

This paper cites Uniref: comprehensive and non-redundant uniprot reference clusters.

Steering Protein Family Design through Profile Bayesian Flow Uniref: comprehensive and non-redundant uniprot reference clusters

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.350601Z

Source-reported events for the cited work

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Observation 2929b012-69a3-4bdc-9c91-a7e4df660075 · outbound

This paper cites Poet: A generative model of protein families as sequences-of-sequences.

Steering Protein Family Design through Profile Bayesian Flow Poet: A generative model of protein families as sequences-of-sequences

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.334572Z

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Observation 76c243c7-7288-47ea-bc06-fcbe7db08ee6 · outbound

This paper cites Attention is all you need.

Steering Protein Family Design through Profile Bayesian Flow Attention is all you need

Reference 48

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Source-reported events for the cited work

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Observation bee38739-76de-43fb-8b48-c39eeb44b643 · outbound

This paper cites Diffusion Language Models Are Versatile Protein Learners.

Steering Protein Family Design through Profile Bayesian Flow Diffusion Language Models Are Versatile Protein Learners

Reference 49

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Source-reported events for the cited work

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Observation 6448caba-4882-4261-93c2-ce97b09d9d08 · outbound

This paper cites Directed evolution: methodologies and applications.

Steering Protein Family Design through Profile Bayesian Flow Directed evolution: methodologies and applications

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.307240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c035b03c-096e-4dd9-9a39-6ef58988f78e · outbound

This paper cites De novo design of protein structure and function with rfdiffusion.

Steering Protein Family Design through Profile Bayesian Flow De novo design of protein structure and function with rfdiffusion

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-08T12:02:09.124874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57aacff1-f5f6-429d-aac3-614596fe91ac · outbound

This paper cites High-resolution de novo structure prediction from primary sequence.

Steering Protein Family Design through Profile Bayesian Flow High-resolution de novo structure prediction from primary sequence

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.278088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6e48c761-0fd4-4345-8d40-23a1195b9ee9 · outbound

This paper cites Masked inverse folding with sequence transfer for protein representation learning.

Steering Protein Family Design through Profile Bayesian Flow Masked inverse folding with sequence transfer for protein representation learning

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.261855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2b5112fd-8e28-42ec-96c5-778551a2c192 · outbound

This paper cites XLNet: Generalized Autoregressive Pretraining for Language Understanding.

Steering Protein Family Design through Profile Bayesian Flow XLNet: Generalized Autoregressive Pretraining for Language Understanding

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-08T12:02:09.138967Z

Source-reported events for the cited work

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Observation d3b2fd68-aff9-445d-bffc-7713d030895d · outbound

This paper cites Enzyme function prediction using contrastive learning.

Steering Protein Family Design through Profile Bayesian Flow Enzyme function prediction using contrastive learning

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.247690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 96e5f1df-ce24-4230-8e41-e98a5cca06d3 · outbound

This paper cites Spearman rank correlation.

Steering Protein Family Design through Profile Bayesian Flow Spearman rank correlation

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.232301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation afb57ce0-c4d7-4777-bd5a-9a0915048769 · outbound

This paper cites Unsupervisedly prompting alphafold2 for accurate few-shot protein structure prediction.

Steering Protein Family Design through Profile Bayesian Flow Unsupervisedly prompting alphafold2 for accurate few-shot protein structure prediction

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.215465Z

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Observation 57a365f9-5740-4062-be37-8983f90d3613 · outbound

This paper cites Enhancing the Protein Tertiary Structure Prediction by Multiple Sequence Alignment Generation.

Steering Protein Family Design through Profile Bayesian Flow Enhancing the Protein Tertiary Structure Prediction by Multiple Sequence Alignment Generation

Reference 58

Resolution: verified exact; local_arxiv, observed 2026-08-08T12:02:09.251859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 99490d84-0ee3-4d33-b569-81e846d61d9f · outbound

This paper cites write newline.

Steering Protein Family Design through Profile Bayesian Flow write newline

Reference 59

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Unavailable: canonical work link unavailable.

Observation a41e77c6-964b-4323-a2f1-200b3d062f7a · outbound

This paper cites @esa (Ref.

Steering Protein Family Design through Profile Bayesian Flow @esa (Ref

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-08T12:02:09.172387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2879a2f-81a2-46e2-991a-ba38c64ee44a · outbound

This paper cites an unresolved cited work.

Steering Protein Family Design through Profile Bayesian Flow Unresolved cited work

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-08T12:02:09.177999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2194fd9-eb15-401b-aa06-89c078e54c77 · outbound

This paper cites - Placeholder or duplicate abstracts will be removed.

Steering Protein Family Design through Profile Bayesian Flow - Placeholder or duplicate abstracts will be removed

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T12:02:22.167820Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Outbound references

Pith citing papers