ActivationGate

Two-signal activation gate implementing the immunological principle that immune cell activation requires both antigen-specific recognition (Signal 1) AND costimulatory context (Signal 2).

Value

An R6Class generator. ActivationGate$new() returns an ActivationGate object.

Details

Prevents spurious activation on isolated outliers. An antibody is only allowed to clone if both signals exceed their thresholds. This is biologically-principled regularization.

Signal 2 options:

• "density": Local data density around the antibody

• "danger": User-provided danger signal vector

• "entropy": Local label entropy (classification only)

Public fields

signal2_type

Type of costimulatory signal.

threshold1

Minimum affinity for Signal 1 (antigen recognition).

threshold2

Minimum costimulatory signal for Signal 2.

danger_signals

User-provided danger signal vector (for "danger" type).

Methods

Public methods

• ActivationGate$new()

• ActivationGate$evaluate()

• ActivationGate$format()

• ActivationGate$clone()

---

Method new()

Create a new ActivationGate.

Usage

ActivationGate$new(
  signal2_type = "density",
  threshold1 = 0.1,
  threshold2 = 0.3,
  danger_signals = NULL
)

Arguments

signal2_type

Character. "density", "danger", or "entropy".

threshold1

Numeric. Minimum affinity threshold.

threshold2

Numeric. Minimum Signal 2 threshold.

danger_signals

Numeric vector. Per-data-point danger scores.

---

Method evaluate()

Evaluate which antibody-data interactions pass the two-signal gate.

Usage

ActivationGate$evaluate(affinity_matrix, X, A, y = NULL, task = "clustering")

Arguments

affinity_matrix

Numeric matrix (n x m) of affinities.

X

Numeric matrix of data (n x d).

A

Numeric matrix of antibodies (m x d).

y

Target vector or NULL.

task

Character. Task type.

Returns

Logical matrix (n x m) where TRUE means the interaction is activated.

---

Method format()

Format a short summary, one element per line. Used by print().

Usage

ActivationGate$format(...)

Arguments

...

Not used.

Returns

A character vector.

---

Method clone()

The objects of this class are cloneable with this method.

Usage

ActivationGate$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

# Two-signal activation gate
data(iris)
X <- as.matrix(iris[, 1:4])
A <- X[sample(150, 10), ]
rep <- ImmuneRepertoire$new(A)
gate <- ActivationGate$new(signal2_type = "density", threshold2 = 0.3)
aff <- rep$affinity_matrix(X, "gaussian")
activated <- gate$evaluate(aff, X, A)
sum(activated)  # number of activated interactions
#> [1] 469