Name: Protein Function Prediction
Author: PharMolix

Protein Function Prediction

Predict protein function and properties from amino acid sequence using BioT5. Use this skill when: (1) You have a protein sequence and want to understand its biological function, (2) You need to identify enzyme activity, pathway involvement, or molecular interactions, (3) You want a concise description of protein properties from sequence alone.

PharMolix1,042 星标2026年3月19日

职业
分类: 科学计算

Predict functional annotations and properties for proteins from their amino acid sequences using the BioT5 model.

When to Use

You have a protein FASTA sequence and need to understand its biological role
You want to identify enzyme function, pathway involvement, or molecular mechanisms
You need quick functional insights without experimental data
You're characterizing novel or unannotated protein sequences

Workflow

from open_biomed.data import Protein, Text
from open_biomed.core.pipeline import InferencePipeline

# Create protein from FASTA sequence
protein = Protein.from_fasta("YOUR_AMINO_ACID_SEQUENCE")

# Create the question for functional annotation
question = Text.from_str(
    "Inspect the protein sequence and offer a concise description of its properties."
)

# Load the BioT5 model for protein question answering
pipeline = InferencePipeline(
    task="protein_question_answering",
    model="biot5",
    model_ckpt="./checkpoints/server/protein_question_answering_biot5.ckpt",
    device="cuda:0"
)

# Run inference to get functional annotation
outputs = pipeline.run(protein=protein, text=question)
function_description = outputs[0][0].str
print(function_description)

Predict functional annotations and properties for proteins from their amino acid sequences using the BioT5 model.

When to Use

You have a protein FASTA sequence and need to understand its biological role
You want to identify enzyme function, pathway involvement, or molecular mechanisms
You need quick functional insights without experimental data
You're characterizing novel or unannotated protein sequences

Workflow

from open_biomed.data import Protein, Text
from open_biomed.core.pipeline import InferencePipeline

# Create protein from FASTA sequence
protein = Protein.from_fasta("YOUR_AMINO_ACID_SEQUENCE")

# Create the question for functional annotation
question = Text.from_str(
    "Inspect the protein sequence and offer a concise description of its properties."
)

# Load the BioT5 model for protein question answering
pipeline = InferencePipeline(
    task="protein_question_answering",
    model="biot5",
    model_ckpt="./checkpoints/server/protein_question_answering_biot5.ckpt",
    device="cuda:0"
)

# Run inference to get functional annotation
outputs = pipeline.run(protein=protein, text=question)
function_description = outputs[0][0].str
print(function_description)

Output Component	Example
Enzyme name	Phosphoribosylformylglycinamidine synthase
Biological pathway	Purine biosynthesis pathway
Catalytic activity	FGAR to FGAM conversion
Complex membership	Part of FGAM synthase complex (PurQ, PurL, PurS)
Mechanism details	ATP-dependent, glutamine amidotransferase activity

Error	Cause	Solution
`FileNotFoundError`	Model checkpoint not found	Download checkpoint to `./checkpoints/server/`
`CUDA out of memory`	GPU memory insufficient	Use smaller batch or CPU device
`Sequence too long`	Exceeds 512 amino acid limit	Truncate sequence or use sliding window

Protein Function Prediction

When to Use

Workflow

Protein Function Prediction

When to Use

Workflow

Expected Outputs

Example Output

Input Formats

Error Handling

Model Details

Limitations

Deep Research

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Protein Function Prediction

When to Use

Workflow

Protein Function Prediction

When to Use

Workflow

Expected Outputs

Example Output

Input Formats

Error Handling

Model Details

Limitations

Related Skills

Deep Research

Data Analyst

Academic Researcher

Data Scientist

Biopython

Binary Analysis Patterns